Assessment of Body Image - Corwin

CHAPTER 4

Assessment of Body Image Hemal P. Shroff, Rachel M. Calogero, and J. Kevin Thompson

T

he field of body image has experienced a phenomenal growth in recent years. In 2004, a new journal, Body Image: An International Journal of Research, was launched by Elsevier to provide a forum for publishing papers in this area. The field of body image was once closely linked to that of eating disorders, but the construct is now often studied in a variety of fields, including, oncology, dentistry, surgery, sociology, nutrition, and obesity (Cash & Pruzinsky, 2002). In addition, measurement of body image in younger samples and men has received a great deal of attention in recent years (Cafri & Thompson, 2007; Yanover & Thompson, 2009). The expansion of the field in general has been paralleled by a dramatic increase in the number of measures developed to assess some dimension of “body image.” In this chapter, we aim to briefly cover the broad categories of measures, discuss recent innovations, and outline important methodological issues. It is not possible for us to discuss all the measures in detail; therefore, we will focus our discussion on those measures that have been widely used and received rather extensive psychometric evaluation. We provide information regarding many of the available measures in Table 4.1. Within the text and in the table, we categorize measures using standard

terminology into the following dimensions of body image: subjective and affective, cognitive, and behavioral. We also include a subsection on new and widely used measures that examine sociocultural and interpersonal influences on body image because of their relevance for assessing associated features of body image disturbance that may have treatment indications. It should be noted that we do not discuss perceptual measures in this chapter because they are seldom used in clinical practice, and there is an ongoing debate regarding whether these measures provide a distinct index of perceptual body image (J. K. Thompson & Gardner, 2002). Also, at the end of this chapter, we offer some detailed guidelines for choosing a measure based on gender, age, and ethnicity. It is important to keep in mind that in selecting a measure, one should always give careful consideration to the psychometric qualities of the instrument and the validation sample for the specific scale. For instance, scales developed with an adult eating disordered clinical sample may not necessarily be appropriate for use with a community sample of adolescents. In Table 4.1, we provide reliability data for the measures that are reviewed. The standard requirement for a scale to have acceptable reliability is a reliability coefficient of (Text continues on page 126) 115

Author(s) Phillips (1996)

Rosen and Reiter (1994)

Mendelson and White (1985); Cecil and Stanley (1997) Mendelson, Mendelson, and White (2001) Williamson, Gleaves, Watkins, and Schlundt (1993) Veron-Guidry and Williamson (1996)

Beebe, Holmbeck, and Grzeskiewicz (1999)

Measure

Body Dysmorphic Disorder Diagnostic Module

Body Dysmorphic Disorder Examination

Body Esteem Scale-Children

Body Esteem Scale–Adolescents and Adults

Body Image Assessment

Body Image Assessment–Children

Body Image Assessment–Revised

TR: 2 weeks, cognitive = .74, affective = .79, desired = .70, cognitivedesired discrepancy = .67, affective-desired discrepancy = .79, affective-desired discrepancy = .63

TR (immediate): current = .94, ideal = .93; (1 week): current = .79, current/ideal = .67

TR: current: .90, ideal: .71

IC: .81–.94

IC: (split half) = .85

IC: .81–.93; R: .87–.94 TR: .87-.94

Kappa: .96

Reliability

Select cognitive and affective body estimates and desired body size from nine female figures that range from underweight to overweight. Normed with college females.

Select current and ideal body shape from nine body figures that range from underweight to overweight.

Select current and ideal body shape from nine female figures that range from underweight to overweight.

Twenty-three items assess three factors in adults and adolescents: appearance, attribution, and weight.

Measures children’s agreement with statements about one’s body.

Interview that assesses multiple components of BDD.

Interview for BDD based on DSM criteria.

Description

Categorical Listing of Body Image Measures With Psychometric and Descriptive Information

Subjective and Affective Measures

Table 4.1

Author(s) Cash, Santos, and Williams (2004); Cash and Grasso (2006)

Cash, Phillips, Santos, and Hrabosky (2004) Thelen, Powell, Lawrence, and Kuhnert (1992) Cash and Fleming (2002)

Huddy, Nieman, and Johnson (1993) Cash, Fleming, and Alindogan (2002)

Measure

Body Image Coping Strategies Inventory

Body Image Disturbance Questionnaire

Body Image and Eating Questionnaire

Body Image Quality of Life Inventory

Body Image Questionnaire

Body Image States Scale

Items assess broad array of aspects of body image disturbance. Fourteen items focus on overweight concerns, dieting, and restraint; for use with younger children. Assesses the impact of one’s body image on 19 life domains using a 7-point Likert-type scale ranging from very negatively (–3) to very positively (+3). Twenty items on a 3-point Likert scale from agree (1) to disagree (3). Measures body image across five different contexts: neutral, negative (day at the beach and magazine models), and positive (party compliments and ideal weight).

IC: .89

IC: all values ≥ .68

IC = .95 TR: 2–3 weeks = .79

TR: 6 weeks: .97

IC: females = .77 (neutral), .90 (negative), .88 (negative), .81 (positive), .80 (positive)

TR: females = .77, males = .72 (Continued)

Twenty-nine items assess how individuals cope with various situations that threaten their body image on a 3-point Likert-type scale; three subscales (Avoidance, Appearance Fixing, Positive-Rational Acceptance).

Multiple studies: IC > .70

IC: males = .62 (neutral), .66 (negative), .78 (negative), .83 (positive), .84 (positive)

Description

Reliability

Author(s) Peterson, Ellenberg, and Crossan (2003)

Petrie, Tripp, and Harvey (2002)

Siegel, Yancey, Aneshensel, and Schuler (1999) Cooper, Taylor, Cooper, and Fairburn (1987); Rosen, Jones, Ramirez, and Waxman (1996) Cuzzolaro, Vetrone, Marano, and Garfinkel (2006)

J. K. Thompson and Tantleff (1992)

Measure

Body Mass Index Silhouette Matching Test

Body Parts Satisfaction Scale–Revised

Body Satisfaction Scale

Body Shape Questionnaire

Body Uneasiness Test (BUT)

Breast/Chest Rating Scale

Table 4.1 (Continued)

TR: current = .85; ideal breast = .81, ideal chest = .69

TR: 1 week = BUT-A = .71–.91 (nonclinical); .80–.94 (clinical): BUT-B = .78–.94 (nonclinical); .68–.92 (clinical)

IC: BUT-A = .79–.90; BUT-B = .69–.90

TR: .88

IC: .73–.80

IC: Study 2, body = .89, face = .74

IC: Study 1, body = .89, face = .76

TR: males’ current = .79, females’ current = .85; males’ ideal = .83, females’ ideal = .82

Reliability

Select current and ideal breast/chest ratings from five male and five female schematic figures, ranging from small to large upper torso.

Thirty-four items assess body shape and/or weight dissatisfaction, behaviors, and feelings, and 37 items assess concern about specific body parts or functions; for males and females.

Thirty-four items assess adult men and women’s concern with body shape and size.

Rate satisfaction with four aspects of pubertal development; for males and females.

Fourteen items assess satisfaction with various body sites on a 6-point Likert-type scale in adult women and men; two factors—body and face.

Interval scale of 27 items along with four gender-specific figures to anchor for older children.

Description

M. A. Thompson and Gray (1995); Wertheim, Paxton, and Tilgner (2004) Furnham and Calnan (1998) McCreary and Sasse (2000); McCreary, Sasse, Saucier, and Dorsch (2004) (1) McCreary and Sasse (2000)

Contour Drawing Rating Scale

Drive for Bulk

Drive for Muscularity Scale (DMS)

Drive for Muscularity–Body Image subscale

Eating Disorder Inventory-2 Body Dissatisfaction subscale

Wooley and Roll (1991)

Color-A-Person Dissatisfaction Test

Garner (1991)

(2) Cafri, van den Berg, and Thompson (2006)

Author(s)

Measure

Uses five colors to indicate level of satisfaction with body sites by masking on a schematic figure for both men and women.

IC: .74–.85

Rate desire to be bigger and to gain weight; for males between ages 16 and 18 years. Fourteen items assess drive for muscularity: MuscleOriented Body Image (MBI; seven items), Muscle-Oriented Behavior (MB; seven items).

Seven items assess satisfaction with appearance (specifically muscular physique); adolescents and young adults.

IC: .70

IC: Full DMS-Males = .85, MBI-Males = .88; MB-Men = .81; Full DMS-Females = .82 (1) IC = .84 (whole scale)

IC >.70 for multiple samples, including individuals with eating disorders and noneating-disordered controls

(2) IC = .90 (subscale)

(Continued)

Nine items assess dissatisfaction with specific body parts.

Select ideal and current self from nine male and nine female schematic figures, ranging from underweight to overweight. (Wertheim sample: adolescents).

TR: .65–.87

TR: 1 week, self = .79

TR: 2 weeks = .72–.84, 4 weeks = .75–.89

Description

Reliability

Author(s) Roth and Armstrong (1993)

Stunkard, Sorenson, and Schulsinger (1983); J. K. Thompson and Altabe (1991)

Goldfarb, Dykens, and Gerrard (1985)

Childress, Brewerton, Hodges, and Jarrell (1993)

Tylka, Bergeron, and Schwartz (2005)

Measure

Feelings of Fatness Questionnaire

Figure Rating Scale

Goldfarb Fear of Fat Scale

Kid’s Eating Disorder Survey

Male Body Attitudes Test

Table 4.1 (Continued) Description Measures the extent to which females feel thin or fat across 61 situations; two subscales: Troubles (38 items) and Satisfaction (23 items). Select ideal and current self from nine male and female figures that vary from underweight to overweight. Normed with college males and females.

Ten items assess overconcern with fatness and body size.

Choose ideal and current self from eight male and eight female figure drawings: for preadolescent childres, Grades 5 to 8. Items relate to weight control behaviors.

Twenty-four items assess body image related to muscularity, body fat, body shape, and height.

Reliability IC: Troubles = .96, Satisfaction = .98

TR: 2 weeks: ideal; males = .82, females = .71, Self-think: males = .92, females = .89, Self-feel; males = .81; females = .83 IC: .70; TR = .88

TR (4 months): .83 for entire survey; not given for figures only

IC: .80–.94; TR: .81–.94

Author(s) Shisslak et al. (1999)

Cash (body-images.com); Brown, Cash, and Mikulka (1990) Mayville, Williamson, White, Netemeyer, and Drab (2002) Hildebrandt, Langenbucher, and Schlundt (2004) Reed, Thompson, Brannick, and Sacco (1991) Petersen, Schulenberg, Abramowitz, Offer, and Jarcho (1984)

Measure

McKnight Risk Factor Survey (MFRS-III)

Multidimensional Body-Self Relations Questionnaire–Appearance Evaluation subscale

Muscle Appearance Satisfaction Scale

Muscle Dysmorphic Disorder Inventory

Physical Appearance State and Trait Anxiety Scale (PASTAS)

Self-Image Questionnaire for Young Adolescents–Body Image subscale

TR: 1 year = .60; 2 years = .44

IC: boys = .81, girls =.77

TR: 2 weeks = .87

IC: trait = .82–.88, state = .82–.92

IC: .77–.85; TR: .81–.87

TR: .76–.89 (subscales)

IC: .74–.79 (subscales);

IC > .70 for multiple samples, including men and women

TR: elementary = .79; middle school = .84; high school = .90

IC: elementary = .82; middle school = .86; high school = .87

Reliability

(Continued)

Eleven items assess positive feelings toward the body in 10- to 15-year-old boys and girls.

Assesses trait or state anxiety associated with 16 body sites (8 weight related, 8 non–weight related).

Thirteen items; three subscales (Desire for Size, Appearance Intolerance, Functional Impairment) in males using a 5-point Likert-type scale.

Nineteen items assess excessive concern with muscularity in males; five subscales (bodybuilding dependence, muscle checking, substance use, injury, and muscle satisfaction).

Seven items assess overall appearance satisfaction.

Five items assess concern with weight and shape; elementary, middle and high school children.

Description

IC = total-women = .88; total-men = .90; self-eval-women = .82; self-eval-men = .84; motivational-women = .90, motivational-men = .91 IC > .70

IC: .94, .95, .96 (three samples, respectively)

Cash, Melnyk, and Hrabosky (2004)

Jakatdar, Cash, and Engle (2006) Spangler and Stice (2001)

Appearance Schemas Inventory– Revised

Assessment of Body Image Cognitions

Beliefs About Appearance Scale

TR: 3 weeks = .83 (Sample 3); 10 months = .73 (Sample 2)

Reliability

Author(s)

(2) TR: females = .35– .75; males = .45–.80

(1) Not available

Measure

Cognitive Measures

(1) Gruber, Pope, Borowiecki, and Cohane (1999)

Somatomorphic Matrix

(2) Cafri, Roehrig, and Thompson (2004)

IC: females = .94–.96; males = .93–.94

Cash (2002)

Situational Inventory of Body Image Dysphoria (SIBID)–Short Form TR: 1 month, females = .87; males = .81

Reliability

Author(s)

Measure


Twenty items assess one’s beliefs about consequences of appearance for relationships, achievement, self-view, and feelings on a 5-point Likert-type scale.

Thirty-seven items assess eight types of distorted thinking about own physical appearance.

Twenty items assess beliefs and assumptions about the importance and influence of appearance in one’s life on a 5-point Likert-type scale; two subscales (Self-Evaluative Saliance [12 items], Motivational Saliance [8 items]); for males and females.

Description

Assesses current and ideal muscularity and body fat dimensions in men and women; available in (1) computer and (2) paper-and-pencil forms.

Twenty items; short form of SIBID. Men and women rate how often they experience negative body image emotions in various situations.

Description

Author(s) Kashima, Yamashita, and Okamoto (2003) Cash, Lewis, and Keeton (1987) Cash and Szymanski (1995) Szymanski and Cash (1995) Schulman, Kinder, Powers, Prange, and Gleghorn (1986) Morrison, Morrison, Hopkins, and Rowan (2004)

Rose, Cooper, and Turner (2006)

Edwards and Launder (2000);

Measure

Body Attitude Test (BAT)–Japanese version

Body Image Automatic Thoughts Questionnaire

Body Image Ideals Questionnaire

Body Image Ideals Questionnaire– Expanded

Bulimia Cognitive Distortions Scale– Physical Appearance subscale

Drive for Muscularity Attitudes Questionnaire

Eating Disorder Belief Questionnaire–Self Acceptance & Acceptance by Others subscales

Swansea Muscularity Attitudes Questionnaire

IC: .86–.92; .58–.70 (for 2-item subscale)

IC: .85 (self-acceptance), .94 (acceptance by others)

IC: .84 (Study 1), .82 (Study 2); .79 (protein supplement), .72 (weight training), .45 (cardio exercise)

IC: .97 (entire scale)

IC: .81–.95

IC: discrepancy = .75; importance = .82

IC: .90

IC: .90

Reliability

(Continued)

Nineteen items assess intention to become more muscular (eight items), positive attributes of muscularity (nine items), and muscle-building activities (two items).

Six items assess how attractive one will feel if one is slim (self-acceptance); nine items assess how others will feel if body is slim/toned (acceptance by others).

Eight items assess attitudes toward muscularity in males.

Measures agreement with 25 statements related to physical appearance-related cognitions.

Ratings of one’s specific attributes from own viewpoint and that of romantic partner based on “ideal” and “actual.”

Ratings of ideal and actual self on 10 attributes related to weight/appearance and strength/importance of attribute.

Measures frequency of 37 negative and 15 positive body image cognitions in women.

Twenty items measure body dissatisfaction.

Description

Reas, Whisenhunt, and Netemetyer (2002)

Rosen, Srebnik, Saltzberg, and Wendt (1991)

Body Checking Questionnaire

Body Image Avoidance Questionnaire

Author(s) Fisher and Thompson (1998) Lundgren, Anderson, and Thompson (2004)

Tantleff-Dunn, Thompson, and Dunn (1995) Stice, Shaw, and Nemeroff (1998)

Measure

Body Comparison Scale

Fear of Negative Appearance Evaluation Scale

Feedback on Physical Appearance Scale

Ideal Body Internalization Scale– Revised

Sociocultural and Interpersonal Influences

Author(s)

Measure

Behavioral Measures


TR: 1 year = .59

IC: .88

TR: 2 weeks = .82

IC: .84

IC = .94

IC: .95

Reliability

IC: .89; TR: 2 weeks = .87

TR: 2 weeks = .94

IC: .88 (overall appearance), .92 (specific body parts), .83 (idiosyncratic checking)

Reliability

Ten items assess agreement with cultural ideal for female body.

Twenty-six items assess verbal and nonverbal appearancerelated commentary on a 5-point Likert-type scale; adults.

Measures affective reaction to perceived negative evaluation by others. The original measure consisted of eight items. In the second study, it was reduced it to 6 items.

Assesses tendency to compare specific body sites with others.

Description

Frequency of body image avoidance behaviors.

Twenty-three items assess body-checking behaviors related to overall appearance, specific body parts, and idiosyncratic checking behaviors in adult females.

Description

McKinley and Hyde (1996); Lindberg, Hyde and McKinley (2006) J. K. Thompson, Cattarin, Fowler, and Fisher (1995) J. K. Thompson, Heinberg, and Tantleff (1991) Noll and Fredrickson (1998)

J. K. Thompson, van den Berg, Roehrig, Guarda, and Heinberg. (2004)

Keery, Shroff, Thompson, Wertheim, and Smolak (2004)

Objectified Body Consciousness Scale

Perception of Teasing Scale

Physical Appearance Comparison Scale

Self-Objectification Questionnaire

Sociocultural Attitudes Towards Appearance Scale–3

Sociocultural Internalization of Appearance Questionnaire– Adolescents

IC: .83–.92 (U.S. and international samples)

IC: .93

NA

IC = .78; TR = .72

IC: general weight = .94, competency = .78

IC: body surveillance: .79–.89; body shame = .75

Reliability

NOTE: BDD = body dysmorphic disorder; IC = internal consistency; TR = test-retest reliability; NA = not available.

Author(s)

Measure

Five items measure thin-ideal internalization in adolescent girls.

Thirty items measure multiple aspects of societal influence on appearance and consists of four distinct subscales: Pressures, Information, Internalization-General, Internalization-Athlete.

Rank order of 10 attributes (5 appearance-based, 5 non–appearance based) based on how important the attribute is to the physical self-concept.

Assesses tendency to compare own appearance with others.

Twelve items assess frequency and emotional response to general weight teasing and competency teasing.

Sixteen items assess body surveillance (eight items) and body shame (eight items); modified version used with preadolescents and adolescents.

Description

126——HANDBOOK OF ASSESSMENT METHODS FOR EATING BEHAVIORS AND WEIGHT-RELATED PROBLEMS

around .70 (J. K. Thompson, 2004). When a measure is considered for clinical or research purposes, it is important to select a measure that has acceptable reliability and validity and has been evaluated on a sample that is similar to the one under consideration. Some measures have received limited validity work, but others have received extensive validation (such as the Eating Disorders Inventory–Body Dissatisfaction scale and the Multidimensional Body Self-Relations Questionnaire; see Cash, 2000; Garner, 2004). In the sections that follow, we discuss measures that fit into widely accepted categorical dimensions of body image, with an intent of providing a broad overview of the possible measures that might be included in an assessment battery. Again, this is a highly selective review, and the reader is also encouraged to examine the broader range of potential measures that are available in Table 4.1.

Measurement Categories Subjective and Affective Measures Subjective and affective measures tap into a dimension of body image that is usually labeled satisfaction (J. K. Thompson, Heinberg, Altabe, & Tantleff-Dunn, 1999). The satisfaction may be site specific (e.g., waist, hips) or may involve a more global self-evaluation of overall appearance. There are two primary methods for assessing the subjective and affective component. One method consists of using figural stimuli consisting of a range of images (usually schematic line drawings or silhouettes) that differ in body size and/or shape. The stimuli are presented to the participants, who are asked to select the image that represents their ideal self and their real (current) self. The discrepancy between their current and ideal selves is used as the index of dissatisfaction. The second category consists of questionnaire measures that typically ask respondents to complete a variety of items designed to assess body satisfaction or an affective dimension of body image. Examples of these two types of measurement strategies (figural

rating scales, questionnaire measures) are provided below. A variety of figural stimuli measures have been created in the past two decades (Table 4.1). A measure that has been developed specifically for children is the Body Image Assessment–Children (Veron-Guidry & Williamson, 1996). This scale is particularly useful as it has separate figures for children and for adolescents, so that the participants make their ratings using figures similar to themselves in body composition and pubertal status. A figural scale that has been used with adult women is the Contour Drawing Rating Scale (J. K. Thompson et al., 1999; M. A. Thompson & Gray, 1995). Two widely used figural scales allow for the assessment of dissatisfaction related to overall weight and muscularity. The Somatomorphic Matrix is a two-dimensional computerized body image test that can be used to assess self and ideal body image in relation to muscularity and body fat (Gruber, Pope, Borowiecki, & Cohane, 1999). The test is available for both genders and consists of 100 images arranged in a 10 × 10 matrix, representing 10 degrees of adiposity and 10 degrees of muscularity. The Somatomorphic Matrix Modification is a paper-and-pencil modification of the original somatomorphic matrix (Cafri & Thompson, 2004c). The Bodybuilder Image Grid (Hildebrandt, Langenbucher, & Schlundt, 2004) is a paperand-pencil measure that has figures arranged in a 6 × 5 matrix with body fat and muscularity varying on two separate dimensions (i.e., six degrees of body fat and five degrees of muscularity). With regard to questionnaire measures, there is also a wide variety available to assess the subjective and/or affective component of body image. Some of these measures are global or generic in nature and provide an overall estimate of body dissatisfaction or focus on specific sites. The Self Image Questionnaire for Young Adults (Petersen, Schulenberg, Abramowitz, Offer, & Jarcho, 1984) includes a subscale that provides a global measure of body satisfaction for adolescents. The Appearance Evaluation subscale of the Multidimensional Body SelfRelations Questionnaire (Cash, 2000) is a measure that has been used in numerous studies, with adult

Assessment of Body Image——127

men and women of different ethnicities (see www.body-images.com). A sample item from this scale is “I like my looks just the way they are.” The Body Shape Questionnaire (Cooper, Taylor, Cooper, & Fairburn, 1987) assesses the experience of “feeling fat” with items such as, “Have you worried about your flesh not being firm enough?” Other measures offer site-specific information regarding satisfaction or body image affect, such as the Body Uneasiness Test (Cuzzolaro, Vetrone, Marano, & Garfinkel, 2006), created for adolescents and adults, which has items that assess concern about specific body parts. Likewise, the Body Dissatisfaction subscale of the Eating Disorder Inventory–3 (Garner, 2004) asks participants to rate satisfaction with nine weightrelevant body sites, including the stomach, hips, thighs, and so forth. This scale has also been widely used with adults and adolescents and has a wealth of normative information for use with individuals with eating disorders. The Body Parts Satisfaction Scale (Petrie, Tripp, & Harvey, 2002) also assesses satisfaction with various body sites in adult men and women. Some scales assess a more specific affective component of body image. For instance, the Physical Appearance State and Trait Anxiety Scale (Reed, Thompson, Brannick, & Sacco, 1991) provides for an assessment of anxiety regarding weight and non-weight-related (hair, eyes, face) body aspects. Cash’s (1994, 2002) Situational Inventory of Body Image Dysphoria scale taps into negative body image–related emotions that accompany exposure to various situations.

& Keeton, 1987) has subscales that assess Positive and Negative body-related cognitions. A relatively new and somewhat unique measure is the Eating Disorder Belief Questionnaire, which contains the Self-Acceptance subscale and the Acceptance by Others subscale (Rose, Cooper, & Turner, 2006). The subscales assess how an individual will feel if her or his body is toned and how others will feel if her or his body is toned. Within this category are a variety of measures related to appearance ideals and self-schema (e.g., Stein & Hedger, 1997; Szymanski & Cash, 1995).

Behavioral Assessment Behavioral measures attempt to document the specific observational manifestation of body image disturbance, such as avoidance or body checking. One of the first measures of this type was a selfreport measure developed by Rosen, Srebnik, Saltzberg, and Wendt (1991), the Body Image Avoidance Questionnaire. The Body Checking Questionnaire (Reas, Whisenhunt, & Netemeyer, 2002) is one of the more recent innovations in this area; a 23-item scale that indexes a variety of bodychecking behaviors. Although only a few questionnaire measures specifically focus on behavioral issues, some of the measures of body dysmorphic disorder (see Table 4.1) provide an assessment of the behavioral component. Interestingly, most of the measures in this category provide a self-report of one’s behaviors—there remains a need for further development of objective measures of behavioral avoidance.

Cognitive Measures

Interview Scales Scales assessing cognitive components of body image include those that evaluate thoughts or beliefs about one’s appearance. For example, Cash, Melnyk, and Hrabosky’s (2004) Appearance Schema Inventory–Revised assesses beliefs about appearance that may reflect a rather ingrained aspect of body image schema. The Body Image Automatic Thoughts Questionnaire (Cash, Lewis,

In addition to the above-mentioned methods of assessment, interview strategies have been used with children, adolescents, and adults. The Eating Disorder Examination (EDE; Fairburn & Cooper, 1993) is a semi-structured interview of eating pathology currently in its 12th edition. The interview has subscales related to body


image (shape and weight concerns). Two interviewers provide symptom ratings in this assessment tool. The interview was originally designed for adults, but Bryant-Waugh, Cooper, Taylor, and Lask (1996) modified the EDE and administered it to children and found that the measure works well with children. The Structured Interview for Anorexia and Bulimic Disorders (SIAB) also has a body image scale as one of its six factors (Fichter, Herpertz, Quadflieg, & Herpertz-Dahlmann, 1998). The Interview for Diagnosis of Eating Disorders–IV (Kutlesic, Williamson, Gleaves, Barbin, & Murphy-Eberenz, 1998) includes symptom ratings for body image disturbance, as well as the other DSM criteria for eating disorders (anorexia nervosa, bulimia nervosa, binge eating disorder, and eating disorder not otherwise specified).

Body Dysmorphic Disorder Body dysmorphic disorder (BDD) is an extreme form of body image disturbance wherein the disparagement of a particular aspect of appearance may be very severe, even delusional. In recent years, a variety of measures have been developed to assess this disorder. For adolescents, the Body Image Rating Scale (BIRS) has been designed to assess the presence and severity of BDD and its associated features (Mayville, Katz, Gipson, & Cabral, 1999). The scale consists of 15 items in a Likert-type format that focuses on cognitive, affective, and behavioral features of BDD. The most widely used interview measure of BDD is the Body Dysmorphic Disorder Examination (BDDE; Rosen & Reiter, 1996), which has 34 items that index symptoms of BDD. The content of the interview includes preoccupation/negative evaluation of appearance, self-consciousness, excessive importance given to appearance in self-evaluation, avoidance of social situations or activities, camouflaging appearance, and body-checking behavior. The Body Dysmorphic Disorder Diagnostic Module (BDDDM) is an interview based on DSM-IV diagnostic criteria that is designed similar to other Structured Clinical Interview for DSM

Disorders (SCID) modules to determine whether a diagnosis of body dysmorphic disorder is appropriate (Phillips, 1996). The BDD modification of the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) is a 12-item interview that assesses severity of BDD symptoms (Phillips, 1996). These items assess BDD-related thoughts, behaviors, insight, and avoidance. Within the field of BDD, Pope and colleagues have identified a clinical disorder that corresponds to a pathological preoccupation with the pursuit of a muscular ideal, referred to as muscle dysmorphia (Pope, Katz, & Hudson, 1993; Pope, Gruber, Choi, Olivardia, & Phillips, 1997). In muscle dysmorphia, a person is described as experiencing cognitive symptoms, including extreme body dissatisfaction and repeated thoughts of not being sufficiently muscular, along with behavioral symptoms such as substance abuse (e.g., use of anabolic steroids), strict dieting, compulsive weight lifting, and mirror checking (Olivardia, 2004). Some of the measures included in Table 4.1 that assess a muscularity component of body image (Drive for Muscularity, Muscle Areas Satisfaction Scale, etc.) are also useful in providing information related to diagnosing muscle dysmorphia.

Recent Advances One of the recent trends in body image assessment work is the development of a variety of measures designed to index constructs that are closely related to body image and/or that might be considered risk factors for the development of body image disturbance. For instance, the Body Image Coping Strategies Inventory (Cash, Santos, & Williams, 2004) looks at how individuals cope with situations that threaten their body image. The Body Image Quality of Life Inventory (Cash & Fleming, 2002) asks respondents about the effect of their body image on a variety of life domains (home, work, etc.). A variety of sociocultural and interpersonal factors, such as media influences and psychosocial pressures (e.g., teasing), have been associated with body image disturbance. Utilization of these


measures may be useful not only for understanding factors that are connected to an individual’s body image but also assist in identifying variables that may be linked to disturbed eating patterns (Levine & Harrison, 2004; J. K. Thompson, van den Berg, Roehrig, Guarda, & Heinberg, 2004). One of the most commonly used measures in this category is the Sociocultural Attitudes Towards Appearance Questionnaire–Third Revision (J. K. Thompson et al., 2004), which measures multiple aspects of societal influence on appearance, including four subscales: Pressures, Information, Internalization-General, Internalization-Athlete. This scale has also been validated for use with clinical eating disorders populations (Calogero, Davis, & Thompson, 2004). Internalization measures that examine the extent to which the “thin ideal” present in the media is internalized by an individual are also in this category of measures (e.g., Sociocultural Internalization of Appearance Questionnaire–Adolescents [Keery, Shroff, Thompson, Wertheim, & Smolak, 2004]; Ideal Body Internalization Questionnaire [Stice, Shaw, & Nemeroff, 1998]). Appearance comparison scales (e.g., the Physical Appearance Comparison Scale [J. K. Thompson, Heinberg, & Tantleff, 1991]) assess the degree to which an individual compares himself or herself with peers, models, and others. Research with these types of measures are frequently used in studies evaluating risk for body image and eating disturbances (e.g., Shroff & Thompson, 2006a, 2006b). Recently developed measures of body objectification are also relevant to the measurement of body image. One commonly used measure in this category is the Objectified Body Consciousness Scale (OBC; McKinley & Hyde, 1996), which includes two subscales related to how individuals respond to cultural pressures to meet appearance ideals. The Body Surveillance subscale assesses the degree to which an individual engages in habitual monitoring of their external appearance. The Body Shame subscale assesses the degree to which an individual feels like a bad person if not meeting societal appearance ideals. The OBC scale has been modified recently to provide a validated measure of objectified body consciousness in preadolescents

and adolescents (Lindberg, Hyde, & McKinley, 2006). The Self-Objectification Questionnaire (Noll & Fredrickson, 1998) provides a short rankorder scale that is used to measure the extent to which an individual values observable appearancebased attributes over nonobservable competencebased attributes as most important to their physical self-concept. Research with these measures has frequently used them to assess the extent to which individuals view their bodies as objects to be looked at and evaluated by others, which, in turn, has been linked to an increased risk for body image and eating disturbances (Calogero, Davis, & Thompson, 2005; Tiggemann & Lynch, 2001; Tiggemann & Slater, 2001). Researchers are also beginning to realize the value of cross-cultural studies of body image. To that end, several studies have examined the relevance and applicability of translating measures created in English into other languages. For example, Kashima, Yamashita, and Okamoto (2003) have translated the Body Attitude Test into Japanese, and Thurfjell, Edlund, Arinell, Hagglof, and Engstrom (2003) have created a Swedish translation of the Body Dissatisfaction subscale of the Eating Disorders Inventory for Children. Both of these scales show good internal consistency in the samples in which they were studied. Rousseau, Knotter, Barbe, Raich, and Chabrol (2005) have used a French version of the Body Shape Questionnaire with university female students. In addition, Lau, Lum, Chronister, and Forrest (2006) have translated the Body Parts Satisfaction Scale and the Body Comparison Scale (Fisher & Thompson, 1998) into Chinese. Yamamiya, Shroff, and Thompson (2008) translated a variety of measures into Japanese. These new measures will allow researchers to assess the same construct across cultures and to perform comparative studies. Such studies may shed some light on factors leading to body image disturbance in various cultures around the world.

Methodological Issues An important consideration about body image scales is whether the clinician or researcher is


attempting to assess a state or trait dimension. In most cases, measures assess traits; however, a few state measures have been developed. Primarily, these measures have been used in experimental studies designed to investigate the impact of specific variables (e.g., exposure to media images) on body image (J. K. Thompson, 2004). These scales could potentially be used in a clinical setting as a gauge of the immediate, within-session improvement in body image. One such measure is the state subscale of the Physical Appearance State and Trait Anxiety Scale (Reed et al., 1991). Cash, Fleming, and Alindogan (2002) have also created the Body Image States scale, which offers the advantage of being rather short (six items) so that it can be used efficiently for multiple ratings. Another methodological issue, touched on early in this chapter, is that some of the measures created for the assessment of some component of body image were standardized on relatively small samples and may have limited evidence of reliability and validity. In addition, the samples are not always clinical in nature (i.e., individuals with a diagnosis of an eating disorder or body dysmorphic disorder). As mentioned earlier, they may have limited generalizability due to limited work with a variety of ages and/or ethnicities. A further limitation of body image measures is that no reliable measures for very young children (i.e., younger than 6 years) have been developed. The ethnicity of the standardization sample should be taken into account. For example, using a figural rating scale, a sample of Moroccan Sahraoui women rated their ideal body size as significantly larger than their rating of an average body size (Rguibi & Belahsen, 2006), which is in contrast to the typical findings among White, European American samples of women. In this sample, greater body dissatisfaction predicted attempts to gain weight as opposed to lose weight. Ethnic differences in response to body image measures have also been observed based on the degree of assimilation and/or acculturation into other cultural contexts. For example, again using figural rating scales, research has indicated that Latina women born in the United

States endorse an even thinner ideal body size than European American women, whereas Latina women who immigrated to the United States endorsed a larger body ideal (Lopez, Blix, & Blix, 1995). Although limited work has assessed levels of different body image dimensions with a variety of ethnic groups, it is important to consider ethnic differences when interpreting individual responses to body image measures and to seek out this information when it is available. The gender and sexual orientation of the standardization sample should also be taken into account. For example, the body objectification measures have been primarily developed for and tested in samples of heterosexual women; however, recent research has provided more information about men’s body surveillance and body shame (Hebl, King, & Lin, 2004), as well as gay men (Martins, Tiggemann, & Kirkbride, 2007) and lesbian women (Kozee & Tylka, 2006), indicating different levels and patterns of relations among body objectification and body image disturbances across these populations.

Conclusions and Practical Considerations We now offer some specific guidelines for selecting a measure. One of the strategies that has guided our decision over the past several years (e.g., J. K. Thompson et al., 1999) is to include a variety of measures that tap into different dimensions of body image disturbance, especially when involved in clinical work. (The decision for research purposes may be more specific and targeted, depending on the research question.) For instance, we generally include at least one measure that assesses a more abstract aspect of appearance (e.g., not weight related or specific to a certain body site). One widely used measure of this aspect of body image is the Multidimensional Body Self-Relations Questionnaire–Appearance Evaluation subscale (MBSRQ-AE; Brown, Cash, & Mikulka, 1990). We also typically include a measure of weight-specific body image, such as the Eating Disorder


Inventory–Body Dissatisfaction subscale. Another measure that might be included is a measure that assesses a variety of different sites, such as the MBSRQ–Body Areas Satisfaction Scale. A nice addition to questionnaire measures is a figural rating scale, such as the Contour Drawing Rating scale (M. A. Thompson & Gray, 1995). The above measures generally index the affective and subjective nature of body image; therefore, it may also be useful to add a measure or two that involves cognitive disturbances (see Table 4.1). These types of measures are very helpful for providing evidence of disturbed thinking patterns that might be addressed in a clinical intervention for body image or related disturbances (e.g., eating disorders). For instance, the Appearance Schemas Inventory–Revised (Cash, Melnyk, & Hrabosky, 2004) and the Assessment of Body Image Cognitions (Jakatdar, Cash, & Engle, 2006) are two measures that appear to have excellent psychometric properties. Especially when dealing with boys or men or an athletic sample, it might be important to include a measure that allows for the specific assessment of muscularity dissatisfaction. As Table 4.1 shows, many of these measures have been developed in recent years, including the Drive for Muscularity Scale (McCreary, Sasse, Saucier, & Dorsch, 2004), Drive for Muscularity Attitudes Questionnaire (Morrison, Morrison, Hopkins, & Rowan, 2004), and others (for a review, see Cafri & Thompson, 2007). If an initial assessment suggests the possible presence of body dysmorphic disorder, it would be important to include a measure that assesses this more severe form of disturbance such as the Body Dysmorphic Disorder Examination (Rosen & Reiter, 1996) or the Body Dysmorphic Disorder Diagnostic Module (Phillips, 1996). There are a few sources that someone interested in the assessment of body image can return to periodically for updates on measures and assessment issues. First, the journal Body Image (Elsevier.com) frequently has articles that include development and validation of new measures. Second, Tom Cash’s Web site (body-images.com)

contains detailed advice on his measures of body image, which are quite numerous. Third, our Web site (bodyimagedisturbance.org) contains information on the measures that we have developed that assess body image and/or related constructs (such as social and interpersonal influences on body image). Fourth, it is very important to stay current with the scientific literature because new measures appear with regularity and old measures are reexamined. For instance, Pook, TuschenCaffier, and Brähler (2008) recently evaluated eight different versions of the Body Shape Questionnaire. Measures are also often modified and evaluated for use with samples cross-culturally; for instance, Yamamiya et al. (2008) recently evaluated several measures on a Japanese sample. Therefore, when considering a measure that has been available for several years, it is often useful to conduct a literature review to see if the measure has been modified and/or whether the measure has received new evaluation with a sample that it may not have been tested upon previously. In conclusion, this chapter has provided a fairly selective review of measures commonly used in the assessment of body image. The clinician or researcher has a rather daunting task when faced with the variety and plethora of measures available for selection. We hope this chapter offers a few guidelines that reduce the complexity involved in the evaluation of body image disturbance.

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136——HANDBOOK OF ASSESSMENT METHODS FOR EATING BEHAVIORS AND WEIGHT-RELATED PROBLEMS Thurfjell, B., Edlund, B., Arinell, H., Hagglof, B., & Engstrom, I. (2003). Psychometric properties of Eating Disorder Inventory for Children (EDI-C) in Swedish girls with and without a known eating disorder. Eating and Weight Disorders, 8, 296–303. Tiggeman, M., & Lynch, J. (2001). Body image across the life span in adult women: The role of selfobjectification. Developmental Psychology, 37, 243–253. Tiggemann, M., & Slater, A. (2001). A test of objectification theory in former dancers and non-dancers. Psychology of Women Quarterly, 25, 57–64. Tylka, T. L., Bergeron, D., & Schwartz, J. P. (2005). Development and psychometric evaluation of the Male Body Attitudes Scale (MBAS). Body Image, 2, 161–175. Veron-Guidry, S., & Williamson, D. A. (1996). Development of a body image assessment procedure for children and preadolescents. International Journal of Eating Disorders, 20, 287–293. Wertheim, E. H., Paxton, S. J., & Tilgner, L. (2004). Test-retest reliability and construct validity of

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CHAPTER 5

Measures of Restrained Eating Conceptual Evolution and Psychometric Update Michael R. Lowe and J. Graham Thomas

R

esearch on restrained eating was first published more than 30 years ago. During this period, much has been learned about the psychometric properties of the three primary measures of restrained eating. One purpose of the present chapter is to supplement and update the thorough review of restraint measures provided by Allison and Gorman in the first edition of this book. We have retained the psychometric information from their chapter and updated it with data published since 1995. Since the first studies on restrained eating were published in 1975 (Herman & Mack, 1975; Herman & Polivy, 1975), another major development has been an evolution—some might say a revolution—in the very meaning of restrained eating. That is, at a conceptual level, it has become clearer what these measures are—and are not— measuring, and these newer findings are often inconsistent with the way in which the measures were originally conceptualized. Because the psychometric properties of a measure only become meaningful when some consensus exists on the

concept or domain assessed by that measure, it is critical to review research that can help specify what restrained eating means and what restrained eating measures are assessing. We first provide a brief historical overview of the three main measures of restrained eating and the rationale for their development. This is followed by a consideration of studies, most of which have been published since the first edition of this book, that have raised questions about what these scales are measuring. The final section provides an update on the psychometric properties of restraint scales, again focusing primarily on the three most widely used measures of restraint.

A Brief History of Measures of Restrained Eating The first measure of restrained eating, the Restraint Scale (RS), was developed by Herman and Polivy (1975) with the final, 10-item revised 137


version published in 1978 (see Herman & Polivy, 1980). The rationale for the development of the RS grew out of the work of Schachter and Rodin (1974) and Nisbett (1972) on factors controlling food intake in the obese. Herman and Polivy (1975) and Herman and Mack (1975) reasoned that normal-weight individuals who were constantly dieting and holding their weight below its biological set point would demonstrate anomalies in eating behavior that resembled those shown by obese individuals in prior research. This reasoning directly followed from Nisbett’s (1972) hypothesis that differences in eating behavior between normal-weight and overweight individuals were due to the overweight individuals keeping their body weight suppressed below its biologically appropriate level to conform to social norms. The RS was used to identify normalweight individuals whose body weight was kept suppressed by constant dieting. Subsequent research has indeed found that the RS identifies normal-weight individuals who differ from unrestrained individuals on a wide variety of behavioral, cognitive, and physiological measures (Herman & Polivy, 1984; Lowe, 1993; Lowe & Kral, 2006). Nonetheless, Stunkard and Messick (1985) noted several serious problems with the RS. First, they reviewed evidence showing that restrained, overweight individuals—unlike normal-weight restrained eaters—did not overeat following consumption of a preload. This contradicted Herman and Polivy’s (1975) assumption that previously observed differences in eating behavior between normal-weight and obese individuals were due to greater dieting in the obese. If this were true, then restrained obese individuals should be at least as susceptible to preload-induced overeating as normal-weight restrained eaters. Second, they noted that the RS measured not only dietary restraint but also weight fluctuations. Weight fluctuation is often higher in obese individuals for reasons having nothing to do with dieting behavior (e.g., if the degree of weight fluctuation that individuals experience is a constant fraction of their body mass, obese individuals will experience larger fluctuations

in absolute terms; see Drewnowski, Riskey, & Desor, 1982). Furthermore, Drewnowski et al. (1982) showed that two weight fluctuation items account for 70% of the variance in total RS scores and also found that obese persons actually scored lower on the dietary concern factor of the RS. These problems led Stunkard and Messick to develop a new measure of restraint—the restrained eating scale— which is one of three factors in their Three-Factor Eating Questionnaire (TFEQ; now called the Eating Inventory [EI]). The TFEQ-R scale represented a major improvement in the assessment of restrained eating because it eliminated two confounds— between dieting and overeating and between restrained eating and overweight—that characterize the RS. Investigators studying restrained eating broadly agree that the TFEQ-R, relative to the RS, represents a “purer” measure of restraint that is more likely to reflect actual efforts to restrict dietary intake (Stunkard & Messick, 1985; van Strien, 1999). van Strien, Frijters, Bergers, and DeFares (1986) noted many of the same problems with the RS that Stunkard and Messick (1985) described. To address these limitations, they developed the Dutch Eating Behavior Questionnaire (DEBQ) that included a restrained eating scale. Their restraint scale is quite similar to Stunkard and Messick’s TFEQ-R measure, in part because both groups used items from a measure developed by Pudel, Metzdorff, and Oetting (1975) to construct their scales. Pudel et al.’s scale assessed “latent obesity” or the tendency of some normalweight individuals to exhibit eating patterns previously associated with obesity. A major advantage of both the TFEQ-R and DEBQ-R scales is that they (unlike the RS) reflect “pure” dietary restraint, permitting the dissociation of restrained eating from its opposite— overconsumption. Interestingly, the TFEQ-R and DEBQ-R scales have weak or nonexistent relationships with the other subscales of the Eating Inventory and DEBQ that tap different types of excessive eating (stemming from disinhibition, hunger, negative emotions, and external food stimuli).

Measures of Restrained Eating——139

Developments in the Definition and Conceptualization of Restrained Eating The majority of early theorizing about restrained eating and its possible psychobiological effects was produced by Herman, Polivy, and their colleagues (Herman & Polivy, 1984). However, during the past 30 or so years, there have been a variety of research findings that have (a) raised questions about the meaning and definition of restrained eating and (b) shed new light on what measures of restrained eating are—and are not— assessing. In the next several sections, we review this literature because it suggests that traditional theorizing about restrained eating and its putative effects is in need of major revision.

The Meaning of Restrained Eating Most researchers have defined restrained eating in a manner similar to the following: Restrained eating refers to conscious efforts to restrict food intake for the purpose of weight control. Over the years, Herman and Polivy have defined the term in different ways, including the suppression of body weight below one’s body weight set point (Herman & Polivy, 1975), the imposition of a cognitively defined “diet boundary” to limit food intake (Herman & Polivy, 1984), and a history of repeatedly going on and off diets, referred to as “unsuccessful dieting” (Heatherton, Herman, Polivy, King, & McGree, 1988). From one perspective, it is certainly possible that a restrained eater on the RS would have all three characteristics implied by these definitions: that her weight would be well below her highest weight ever (and perhaps therefore well below her body weight “set point”), that she would impose a diet boundary on her eating to establish permissible caloric intake, and that she had been on and off diets repeatedly in the past. However, as Lowe (1993) pointed out, these are characteristics that could also be used to differentiate three different types of restrained eaters: those who

(a) are well below their highest weights ever by virtue of intentional weight loss (weight suppressors), (b) are currently on a diet to lose weight (current dieters), or (c) have engaged in repeated cycles of dieting and overeating in the past (frequent dieters and overeaters). Importantly, even though most restrained eaters will be characterized by one or more of these designations, these three types of dieting are theoretically independent: Knowing a person’s status on any one of these three dieting types does not necessarily tell you anything about his or her standing on the others. Furthermore, because these different dieting patterns are associated with different appetitive and behavioral responses, Lowe pointed out that measuring a single construct of “restraint” could conceal important differences between these dieting subtypes. For instance, Lowe, Whitlow, and Bellwoar (1991) found that restrained eaters who were not currently dieting ate somewhat more with than without a preload, whereas current dieters ate much less with than without a preload. Another example comes from Lowe, Thomas, Safer, and Butryn (2007), who recently reported that weight suppression was positively associated with binge-eating frequency among individuals diagnosed with bulimia nervosa (which is consistent with Russell’s [1979] original theorizing about the role of significant weight losses in bulimia), whereas scores on the Eating Disorders Examination–Restrained Eating subscale were negatively associated with binge-eating frequency (which is inconsistent with the cognitive-behavioral model of bulimia). Another major development regarding the meaning of restraint involves the motivation underlying restrained eating. At different times, Herman and Polivy have viewed restrained eating as a way of examining the effects of dieting to avoid weight gain (Herman & Polivy, 1975), as a factor contributing to weight gain and obesity (Polivy & Herman, 1983), and as a major cause of eating disorders (Polivy & Herman, 1985). Despite these wide variations in the purported significance of restrained eating, the same scale (the RS) has been used to measure restraint, and


essentially the same theory (that dieting behavior sows the seeds of its own destruction) has been used to account for these varied functions of restrained eating. However, when particular subtypes of dieting are examined in relation to outcomes traditionally studied in the restraint literature, the need to go beyond the use of a single, monolithic measure of restraint emerges again. For example, weight suppressors, who, according to the set point model (Herman & Polivy, 1975), should be hyperresponsive to appetitive stimuli, instead show rigorous eating control following a preload (Lowe & Kleifield, 1988) and reduced sweetness preferences (Kleifield & Lowe, 1991). When applied to those with bulimia nervosa, restraint theory predicts that bulimic individuals who are currently dieting should binge more than bulimic nondieters; instead, the opposite relationship has been found in two studies (Lowe, Gleaves, & MurphyEberenz, 1998; Lowe et al., 2007). These findings indicate that the advisability of using the RS to study restrained eating depends on the investigator’s research objectives. If the objective is to study “restrained eating” as operationalized by the RS (which involves the simultaneous measurement of several constructs—dieting, overeating, weight fluctuations, overweight), then the RS could be appropriate to use—and has the advantage of being characterized by a large corpus of previously published findings. (Alternatively, investigators are increasingly using a combination of the TFEQ-R and disinhibition scales from the EI [e.g., Westenhoefer, Broeckmann, Munch, & Pudel, 1994; Williamson et al., 1995]—based on the reasonable assumption that those who score high on both resemble restrained eaters measured by the RS—because this approach permits them to study both the independent and interactional relationship of restrained eating and predisposition toward overeating on outcomes of interest.) If the objective of a study is to examine particular types of dieting, on the other hand, then an alternative to the RS should be considered—for example, by measuring one of the three types of dieting behavior outlined by Lowe (1993) or by putting

people on short-term weight loss diets (Presnell & Stice, 2003).

What Are Restraint Scales Measuring? As noted above, Herman and Polivy (1975) originally conceived of restrained eaters as individuals who were “constantly dieting and concerned with not gaining weight, and who presumably would gain substantial weight if they were to ‘let themselves go’” (p. 667). Although these authors subsequently de-emphasized this characterization of restrained eaters in favor of a more cognitively focused perspective (Herman & Polivy, 1984) that emphasized drive for thinness (Polivy & Herman, 1987), it appears—as we shall see shortly—that this original viewpoint may actually best capture the nature of restrained eaters’ vulnerability to aberrations in their appetitive and consummatory responses. Twenty-five years ago, when no one realized that developed countries were entering the early stages of explosive growth in the prevalence of obesity, dieting in normal-weight individuals (and normal-weight women in particular) was assumed to reflect an unhealthy need to achieve a slim body to conform with societal norms of attractiveness (Striegel-Moore, Silberstein, & Rodin, 1986). As Polivy and Herman put it in 1987, “Nowadays, women are induced to strive toward a condition of ruddy-cheeked emaciation” (p. 635). This emphasis on attaining the “thin ideal” has been widely accepted as the primary driver of restrained eating among individuals in the normal weight range. Thus, restraint theory has gone 180 degrees from its original belief that restrained eating is motivated by an effort to prevent weight gain (Herman & Polivy, 1975) to the belief that it is motivated by the yearning for an unrealistically thin body (Polivy & Herman, 1987). These seemingly contradictory possibilities might be clarified by drawing two distinctions regarding restrained eaters’ motivation for weight control. The first distinction involves restrained


eaters’ goals for weight change. Restrained eaters have elevated levels of body dissatisfaction (Ruderman & Grace, 1988) and both desire a thinner body (Polivy & Herman, 1987) and fear weight gain (Vartanian, Herman, & Polivy, 2005). Presumably, most restrained eaters would like to consume fewer calories than they expend and lose some weight, thereby moving closer to their desired goal and further away from the feared outcome of weight gain. However, Polivy and Herman’s assumption that restrained eaters are driven to reach unhealthy levels of body weight conflates restrained eaters’ desire to be thinner (e.g., to lose a few pounds) with their desire to be objectively thin (e.g., to achieve a body weight far below their medically appropriate weight for their height). A recent study (Chernyak & Lowe, 2007) compared unrestrained and restrained eaters on drive for thinness, fear of fatness, and drive to be objectively thin (defined as being 15% below their medically appropriate weight for height). Restrained eaters scored significantly higher than unrestrained eaters on the first two measures but did not differ from unrestrained eaters on the third measure. These findings suggest that while restrained eaters would like to avoid weight gain or to lose a small amount of weight, they do not have an unhealthy drive to become pathologically thin. Therefore, it appears that restrained eaters are not as strongly motivated to lose weight as has often been assumed. The fact that most restrained eaters are not currently dieting to lose weight (Lowe, 1993) is consistent with this conclusion. The second distinction involves the extent to which restrained eaters, whatever their weight control goals, are actually reducing their caloric intake. Restrained eaters assessed with the RS are assumed to vacillate between periods of caloric restriction and overindulgence without losing weight in absolute terms (Heatherton, Polivy, & Herman, 1991). Restrained eaters on the other two restraint measures are generally assumed to be more successful at caloric restriction, especially since these measures are viewed as purer measures of the actual cognitions and behaviors involved in dieting (Stunkard & Messick, 1985; van Strien,

1999). However, although past lab studies sometimes found that restrained eaters consume less food than unrestrained eaters, recent evidence indicates that restrained eaters, no matter how they are identified, do not eat less in the natural environment than unrestrained eaters (Stice, Cooper, Schoeller, Tappe, & Lowe, 2007). Stice, Fisher, and Lowe (2004) examined five dietary restraint scales that were developed to assess intentional dietary restriction for the purposes of weight control. These scales showed weak and generally nonsignificant correlations with objectively measured caloric intake during unobtrusively observed eating episodes across four studies (mean r = –.07; range: –.34 to .20; Stice et al., 2004). For example, the average correlation between three dietary restraint scales and observed caloric intake of students consuming meals in a cafeteria was –.09. In response to these validity findings, van Strien, Engels, van Staveren, and Herman (2006) noted that short-term caloric intake may not be representative of long-term caloric intake and suggested that researchers test whether dietary restraint scales show inverse correlations with objective measures of longer term caloric intake. Four previous studies (reviewed in Stice et al., 2007) that examined this question found no relationship between caloric intake and several measures of restrained eating. In a recent follow-up study, Stice et al. (in 2007) reported on three additional studies that found that the TFEQ-R scale was not correlated with doubly labeled water-estimated energy intake over 2-week periods or with observationally measured caloric intake over 3 months. Taken together, the foregoing findings suggest that dietary restraint scales may not be valid measures of naturalistic dietary restriction and imply the need to reinterpret findings from studies that have used dietary restraint scales. As Lowe and Levine (2005), Lowe and Butryn (2007), and Stice et al. (2007) have recently suggested, part of this reinterpretation should be based on the idea that measures of restrained eating reflect relative dietary restriction (i.e., relative to the positive energy balance


that would result if a restrained eater no longer practiced restraint) rather than absolute dietary restriction (i.e., relative to energy balance or to the intake of unrestrained eaters). Two other teams of researchers have come to similar conclusions. First, Gorman, Allison, and Primavera (1993) and Allison, Kalinsky, and Gorman (1992) conducted a factor analysis of the TFEQ-R scale and found that it contained two factors that they called cognitive restraint and behavior restraint. They analyzed their data using nonlinear techniques that take into account situations where items differ substantially in their endorsement rates. Their results suggested that the TFEQ-R items form a continuum that begins with relatively common thoughts of reducing eating and ends with overt, deliberate, but relatively rare actions to reduce eating. These results indicate that even measures that ostensibly reflect “successful” restraint do not identify individuals who eat less than unrestrained eaters. Second, Larsen, van Strien, Eisinga, Herman, and Engels (2007) recently factor analyzed the DEBQ-R among a large sample of weightconcerned individuals and found that a twofactor solution fit the data well. The two factors differentiated between restrained eating intentions and restrained eating behavior. In line with Allison et al.’s (1992) work, they found that participants scored higher on dieting intentions than dieting behavior. They also found that that more restrained eating behavior was related to “less external and emotional eating, whereas more restrained intentions (without restrained behavior) were related to more external and emotional eating” (p. 106). These results are reminiscent of the distinction Lowe et al. (1991) made between restrained eaters who are and are not currently dieting to lose weight, with the former group showing a counterregulatory eating pattern and the latter group showing eating regulation. We should also note that the same questions about the relationships between food restriction, overeating, and weight control have been raised in research in children. Birch, Fisher, and Davison (2003) found that 5-year-old girls whose mothers

reported using restrictive feeding practices were more likely to exhibit eating in the absence of hunger at 9 years of age. This was especially true of girls who were already overweight at the age of 5. These results are suggestive of a gene-byenvironment interaction in which overweight girls are genetically predisposed to be highly sensitive to environmental influences over eating. There is no way of knowing from these data whether mothers’ restrictive eating practices are causally related to later vulnerability to eating in the absence of hunger, if they reflect mothers’ concerns about concurrent weight gain in their children and have no causal influence, or if this relationship is due to some as yet unidentified variable. All the research reviewed in this section suggests that, despite their desire to be thinner, in functional terms, most restrained eaters are at best employing restraint to avoid weight gain, not to lose weight. This conclusion is supported by research showing that measures of restrained eating prospectively predict weight gain rather than weight loss (French, Jeffery, & Wing, 1994; Klesges, Isbell, & Klesges, 1992; Stice, Presnell, Shaw, & Rohde, 2005). It appears that, just as most obese individuals who lose weight via dieting eventually regain it (Sarwer & Wadden, 1999), restrained eating may forestall but usually does not prevent weight gain. One additional reason to suggest that much of restrained eaters’ motivation for weight control stems from concerns about gaining weight is that restrained eaters show levels of certain hormones (e.g., reduced leptin, increased cephalic phase insulin) that makes them metabolically predisposed toward weight gain (Lowe & Kral, 2006). Although these findings theoretically could be due to metabolic adaptations to weight loss dieting, the evidence reviewed above indicates that restrained eaters are not in negative energy balance. In sum, it appears that our understanding of the nature of the motivation that has fueled the tremendous increase in dieting behavior in the past few decades has come full circle. Herman and Polivy (1975) started out believing that restrained eating was driven by the desire to avoid weight gain secondary to being


below one’s biologically determined body weight set point value. If one replaces the notion that a body weight set point is “pulling” weight upward from within (e.g., via the hypothalamus [Nisbett, 1972]) with the idea that an obesogenic environment is “pulling” weight upward from without (Lowe & Butryn, 2007; Lowe & Levine, 2005) then Herman and Polivy’s original theorizing appears to be closest to the truth. That is, normal-weight restrained eaters and dieters appear to have a predisposition toward weight gain in an obesogenic environment (e.g., Lowe et al., 2006), but this characteristic would presumably remain latent in environments where food was difficult to come by. From this perspective, the fact that the first research on restrained eating was conducted around the same time that the obesity epidemic began is probably no coincidence. One caveat is needed before bringing this section of the chapter to a close. The fact that

measures of restrained eating generally do not reflect caloric restriction or weight loss dieting should not be taken to mean that diet-induced weight loss is not a risk factor for the development of eating disorders. On one hand, it does appear that the multiple findings in the literature showing that measures of restrained eating or dieting prospectively predict increased bulimic symptoms are not due to low-calorie dieting (Stice et al., 2007). On the other hand, there is good evidence that extreme dieting that produces rapid, extensive weight loss may indeed help cause bulimia nervosa (Butryn & Wadden, 2005; Garner & Fairburn, 1988; Keys, Brozek, Henschel, Mickelsen, & Taylor, 1950; Russell, 1979). These findings are a further indication that it behooves researchers to think carefully about precisely what construct they are interested in investigating when studying “restrained eating” and to tailor their measures of that construct accordingly.

Herman and Polivy’s Restraint Scale Description Herman and Mack (1975) originally developed the Restraint Scale (RS) to identify normalweight individuals who attempt to limit their food intake in an effort to resist biological pressures toward weight gain. The original scale consisted of 5 items measuring chronic dieting. The items were rationally derived and selected for face validity. The scale was tested on a sample of 45 women, which produced a Cronbach’s alpha coefficient of 0.65. Herman and Polivy (1975) revised the instrument to include 11 items, with 6 items forming a Diet and Weight History subscale (alpha coefficient 0.62) and the remaining 5 items forming a Concern With Dieting subscale (alpha coefficient 0.68). The subscales correlated at 0.48, and the alpha coefficient for the whole scale was 0.75. The final iteration of the RS (Herman & Polivy, 1980) consists of 10 items. Polivy, Herman, and Howard (1988) describe the RS as “a 10-item self report questionnaire assessing weight fluctuations, degree of chronic dieting, and related attitudes toward weight and eating” (p. 377). The preponderance of published research using the RS has used this 10-item version. Herman and Polivy (1975) subdivided the RS into two subscales. The Weight Fluctuation (WF) subscale (Items 2, 3, 4, and 10) measures both instability in weight and a history of overweight. The Concern for Dieting (CD) subscale (Items 1, 5, 6, 7, 8, and 9) assess preoccupation with food, overconcern about eating, and overeating tendencies. Thus, an individual who scores highly on both subscales is likely to be characterized by a history of overweight, a desire to weigh less, and unstable body weight. Notably, the RS should not be considered a measure


of actual hypocaloric dieting or energy deficit (Polivy et al., 1988). High scores on the RS are prospectively associated with greater fluctuations in body weight (Heatherton, Polivy, & Herman, 1991; Tiggemann, 1994). Some (Heatherton et al., 1988) have cited the link between restraint scores and weight fluctuation as support for the idea that the concept of restraint should include efforts to restrict eating to control one’s weight and the periodic failure of restraint resulting in episodes of overeating (i.e., disinhibited eating). The RS is consistent with this formulation of restraint and the associated theory that dieting is a major cause of overeating and eating disorders (Polivy & Herman, 1985). As noted previously, this theory has undergone increased scrutiny (e.g., Lowe & Kral, 2006; Stice et al., 2007).

Sample The RS was initially tested on samples of 42 (Herman & Mack, 1975) and 45 (Herman & Polivy, 1975) female college students. The great majority of psychometric studies using the RS have been done with normal-weight and overweight female college students. It is occasionally used with eating-disordered individuals but rarely with clinical populations of overweight individuals.

Norms Studies that incorporate the RS as a measure of primary interest tend to use the RS in one of two ways: either as a continuous measure of restrained eating or as a tool to dichotomize a sample into restrained and unrestrained eaters. In the former case, the RS is typically analyzed with regression methods to investigate constructs that may be associated with restraint. This analytic strategy is desirable because it preserves the full variability of the RS. In the latter case, after participants have been classified as restrained eaters or unrestrained eaters, the two groups are compared on some measure(s), often in an analysis of variance (ANOVA). Historically, the latter approach was more common than the former. Typically, a median split was used to create groups of restrained and unrestrained eaters of approximately equal size. However, medians varied across samples, which resulted in different cutoffs for identifying restrained eaters. Concern over the failure to consistently identify a homogeneous set of restrained eaters across studies led some researchers to adopt the most frequently observed RS median (a score 15) as the standard cutoff for use in studies of restrained eating. This approach has the strength of standardization of the definition of restrained eaters but also the weakness of using dissimilar strategies of defining restrained eating in earlier and later studies of this construct. Furthermore, there is some evidence that medians on the RS are decreasing over time (e.g., medians were in the 15–17 range in the 1970s but are most often in the 12–14 range more recently), which casts doubt on the utility of a preselected cutoff to identify restrained eaters. Table 5.1 presents sample sizes, means, and standard deviations for the RS, as well as its subscales, for a variety of samples. The average score for normal-weight women (mostly from samples of college students) is about 13. The corresponding value for men is 10. These values are useful for determining whether a particular sample is unusually high or low on restraint. It is important to keep in mind that RS scores may differ by nationality, weight status, eating disorder status, or other personal characteristics.

Measures of Restrained Eating——145 Table 5.1

Mean Restraint Scale Scores Reported in the Literature

Scale and Participants

Author

n

Mean

SD

103 99

14.6 11.0

5.5 5.0

120

20.5

4.6

46

13.4

6.0

901

15.1

7.0

617 282

16.4 12.3

6.9 6.4

Whole scale American adults

French, Jeffery, and Wing (1994)

Female Male American adult women

Timmerman and Gregg (2003)

American overweight adults

Williamson et al. (2007)

American college students

Allison, Kalinsky, and Gorman (1992)

Female Male American college students Female Male American college students Female Male

Boerner, Spillane, Anderson, and Smith (2004)

Klem, Klesges, Bene, and Mellon (1990)

215 214

13.0 8.9

6.1 5.5

497

12.6

5.9

346

13.4

5.8

151

10.8

5.8

American female college students

Urland and Ito (2005)

82

13.8

6.6

Australian female college students

Griffiths et al. (2000)

82

12.1

6.0

British adolescent women

Cole and Edelmann (1987)

184

10.6

5.9

British women

Wardle and Beales (1987)

102

13.5

5.4

British men


45

8.5

5.8

Canadian college students

Oates-Johnson and DeCourville (1999)

220

11.6

6.6

159 61

12.8 8.5

6.5 5.7

159 61

12.8 8.5

6.5 5.7

Female Male Canadian college students

Rotenberg and Flood (2000)

Female Male Dutch obese women

Westerterp-Plantenga, Kempen, and Saris (1998)

57

20

3.5

Portuguese female college students

Scagliusi et al. (2005)

62

11.3

5.0

(Continued)

146——HANDBOOK OF ASSESSMENT METHODS FOR EATING BEHAVIORS AND WEIGHT-RELATED PROBLEMS Table 5.1 (Continued) Scale and Participants

Author

n

Mean

SD


15

17.3

9


24

28.1

13.0

Overweight American adults


46

6.9

3.2


Allison et al. (1992)

901

5.8

3.3

617 282

5.9 5.3

3.3 3.5

215

5.3

2.9

214

4.8

3.3

346 151

5.0 4.8

Portuguese women With anorexia nervosa With bulimia nervosa Weight fluctuation scale

Female Male American college students

Boerner et al. (2004)


Klem, Klesges, Bene, et al. (1990)

Female Male British adolescent women


184

4.1

2.8

British women


102

4.9

2.8

British men


45

3.1

3.1

American adults


46

6.4

4.7



901

9.3

4.7

617 282

10.4 6.9

4.6 3.9

215 214

7.7 4.0

3.9 3.2

346 151

8.4 5.9

4.0 3.4

Concern with dieting scale





Female Male British adolescent women


184

6.2

3.5

British women


102

7.8

3.7

British men


45

4.7

3.0


It appears that the practice of dichotomizing individuals into restrained and unrestrained eaters as the primary method of analysis should be discontinued. Stein (1988) demonstrated that an ANOVA design in which participants are dichotomized into groups based on RS score may have less predictive power in a preload study than a regression model in which RS scores are treated as continuous. Maxwell and Delaney (1993) confirmed that using median splits to form factors in a grouped design reduces statistical power. The authors also reported that dichotomizing participants based on a median split may produce erroneous conclusions about interactions among factors. This is especially relevant, as interactions between restraint status and various disinhibiting stimuli form the basis of many studies on restrained eating. Allison, Gorman, and Primavera (1993) discussed the disadvantages of dichotomization in general. Given these findings, the use of full RS scores in regression models is encouraged over the dichotomization of participants into restraint groups based on a median split. An exception may be made in situations where a strong theoretical or empirical basis exists for identifying specific groups of participants based on their RS score. Furthermore, though treating restraint scores continuously is preferable, because the majority of studies have treated restraint as a dichotomy, it is a good idea for researchers to analyze their results both ways so the categorical results can more easily be compared with past studies. A final reason to analyze results dichotomously in secondary analyses is that certain outcomes showing a nonlinear distribution may produce significant results using a median split but not with using continuous scores.

Age There are a dearth of studies examining the relationship between the RS and age. Two studies including college students ranging from ages 17 to 57 years failed to find a relationship between RS and age (Allison et al., 1992; Klem, Klesges, Bene, & Mellon, 1990). However, little can be concluded from these studies because the most participants were between the ages of 18 and 22 years. The point in the human life span when dietary restraint typically asserts itself is unknown. A study by Cole and Edelmann (1987) observed a typical distribution of restraint scores in a sample of adolescent women with a mean age of 15 years old (see Table 5.1).

Gender Boerner, Spillane, Anderson, and Smith (2004) observed higher RS total scores and CD subscale scores, but not WF subscale scores, among college women as compared with men. This pattern was also found by Allison et al. (1992). Klem, Klesges, Bene, and Mellon (1990) found that college women scored higher than men on the CD subscale but not the WF subscale or total RS. Oates-Johnson and DeCourville (1999) reported that college women scored significantly higher than men on the RS. This pattern was also observed by Rotenberg and Flood (2000). French et al. (1994) found that women scored higher on the RS than men in a sample of 202 adults, about a quarter of whom reported that they were actively dieting to lose or maintain weight. In a sample of adults, Klesges et al. (1992) reported higher restraint score in women than men. Thus, women appear to report systematically greater restraint on the RS than men. Concern for dieting seems to be more responsible for this difference than a history of weight fluctuation.


Reliability Internal Consistency The RS has been shown to have good internal consistency (Cronbach’s alpha greater than .75) when used with normal-weight, non-eating-disordered samples. Table 5.2 illustrates the lower alpha levels that are observed in overweight and eating-disordered groups. This difference in alphas is likely attributable to restricted range within the overweight and eatingdisordered subgroups. Crocker and Algina (1986) point out that Pearson product-moment correlations are lower when the variance of one or more variables in the analysis is restricted. As alpha depends on both the number of items and the correlation between items, subgroups of participants who respond in a systematically similar manner will produce lower alphas than more diverse subgroups that show greater variability in their scores. Drewnowski et al. (1982) were the first to point out that overweight and obese individuals are likely to score highly on the RS, and specifically the WF subscale, as a result of large weight fluctuations due, at least in part, to their increased adipose tissue rather than to restrained eating or concern about their weight. This potential measurement artifact may be a further source of homogeneity and subsequent lower internal consistency among overweight samples. The CD and WF subscales show predictably lower alpha levels than the full RS score, presumably due to their smaller number of items. The alphas range from .66 to .71 for the CD subscale and from .70 to .80 for the WF subscale (Allison et al., 1992; Herman & Polivy, 1975; Klem, Klesges, Bene, & Mellon, 1990). van Strien, Breteler, and Ouwens (2002) and van Strien, Herman, Engels, Larsen, and van Leeuwe (2007) examined the internal consistency of the CD and WF subscales after removing Item 6 because of possible criterion confounding (Stice, Ozer, & Kees, 1997) and Item 10 because of inconsistent subscale factor loadings (Blanchard & Frost, 1983; Lowe, 1984; Overduin & Jansen, 1996). The resulting alphas for a group of 209 Dutch female college students were .77 for the five CD items and .70 for the three WF items (van Strien et al., 2002). van Strien et al. (2007) replicated the analysis with 349 normal-weight Dutch female college students and 409 overweight Dutch women and found alphas of .81 and .68 for the altered CD and WF scales for the normal-weight students and alphas of .65 and .72 for the altered CD and WF scales for the overweight women. Boerner et al. (2004) found that alphas for the total RS and its subscales are slightly higher for women than men. Klem, Klesges, Bene, et and Mellon (1990) determined that alphas for the RS and its subscales are equivalent for men and women, as well as for Blacks and Whites.

Test-Retest Reliability RS scores appear to be stable over time (see Table 5.3). A somewhat lower coefficient was obtained with the Scagliusi et al. (2005) Portuguese translation of the RS.

Validity There are a multitude of studies linking the RS to various aspects of eating behaviors, psychopathology, personality factors, and other constructs. It is beyond the scope of this chapter to review all of these reports; furthermore, most of them were not designed to test the validity of the RS. Rather, studies have been included that were (a) designed explicitly to test the


Reliability of Dietary Restraint Scales: Internal Consistency

n

Coefficient alpha


823

.83

Normal-weight college students


78

.72

Obese college students


901

.82

Above two samples combined

Boerner, Spillane, Anderson, and Smith. (2004)

214

.76

Male college students


215

.82

Female college students

Laessle, Tuschl, Kotthaus, and Pirke (1989)

60

.78

Normal-weight women 18 to 30 years old; mostly college students

Rudderman (1983)

89

.86

Normal-weight female college students

Rudderman (1983)

58

.51

Obese female college students

W. G. Johnson, Lake, and Mahan (1983)

51

.79

Normal weight

W. G. Johnson et al. (1983)

58

.50

Obese nondieters


27

.83

Obese dieters

Reference

Sample Characteristics

RS


26

.57

Bulimic women 13 to 41 years old

Klem, Klesges, Bene, and Mellon (1990)

497

.78

College students (151 men; 346 women)


124

.68



373

.78

Normal weight college students

Oates-Johnson and DeCourville (1999)

220

.84


Ouwens, van Strien, van der Staak (2003)

209

.83



58

.78



319

.77


Urland and Ito (2005)

82

.85


van Strien, Cleven, and Schippers (2000)

200

.73


van Strien, Herman, Engels, Larsen, and van Leeuwe (2007)

349

.84


van Strien et al. (2007)

409

.73

Overweight, nonobese women

(Continued)

150——HANDBOOK OF ASSESSMENT METHODS FOR EATING BEHAVIORS AND WEIGHT-RELATED PROBLEMS Table 5.2 (Continued)

n

Coefficient alpha


823

.91



78

.88



901

.90



214

.89



215

.90


Laessle et al. (1989)

60

.80


Ouwens et al. (2003)

209

.88


Ricciardelli, Tate, and Williams (1997)

171

.91


Simmons, Smith, and Hill (2002)

392

.87

American female 7th graders

Simmons et al. (2002)

300

.88

American female 10th graders

Stunkard and Messick (1988)

45

.92

Unrestrained eaters


53

.79

Restrained eaters


98

.93



200

.80



823

.95



78

.91



901

.95


Banasiak et al. (2001)

393

.94

Grade 9 female adolescents


60

.89


Ouwens et al. (2003)

209

.94


van Strien, Frijters, Bergers, and Defares (1986)

114

.94

Obese adults (71 men; 73 women)

van Strien, Frijters, et al. (1986)

996

.95

Normal-weight adults (427 men; 569 women)

van Strien, Frijters, et al. (1986)

1169

.95



200

.94



349

.93



409

.89


Reference


TFEQ-R

DEBQ-R

NOTE: DEBQ-R = Dutch Eating Behavior Questionnaire–Restraint subscale; RS = Restraint Scale; TFEQ-R = Three-Factor Eating Questionnaire–Restraint scale.


Reliability of Dietary Restraint Scales: Test-Retest Reliability

Reference

n

Coefficient

Interval



34

.95

2 weeks

College students

Hibscher and Herman (1997)

86

.92

“A few weeks”


Polivy, Herman, and Howard (1988)

514

.93

1 week


Kickham and Gayton (1977)

44

.93

4 weeks

Normal-weight college students (16 men; 28 women)

305

.74

2½ years

98 men, 207 women

50

.64

1 month



34

.91

2 weeks

College students

Bond, McDowell, and Wilkinson (2001)

64

.81

1 year

College students


17

.93

4 weeks

College students

34

.92

2 weeks

College students

165

.85

4 to 5 weeks

High school students

RS

Klesges, Klem, Epkins, and Klesges (1991) Scagliusi et al. (2005) TFEQ-R

DEBQ-R Allison et al. (1992) Banasiak et al. (2001)

NOTE: DEBQ-R = Dutch Eating Behavior Questionnaire–Restraint subscale; RS = Restraint Scale; TFEQ-R = Three-Factor Eating Questionnaire–Restraint scale.

validity of the RS or (b) report results that may be interpreted after the fact as support for, or evidence against, the theoretical assumptions that serve as a foundation for the development and continued use of the RS.

Content Validity The RS was originally designed to be used with normal-weight individuals. Furthermore, factoranalytic studies of the Restraint Scale often obtain different factor solutions as a function of the number of overweight participants in the sample. Thus, studies including a large proportion of overweight participants are covered in their own section below.


Factorial Composition in Primarily Normal-Weight Samples The two-factor model of the RS, including the CD and WF subscales that Herman and Polivy (1975) identified during the original development of the RS, is the most widely validated and frequently used conceptualization of the measure. This model has been supported by a variety of studies, including primarily normal-weight participants (Allison et al., 1992; Blanchard & Frost, 1983; Cole & Edelmann, 1987; Drewnowski et al., 1982; Heatherton et al., 1988; Lowe, 1984; Polivy et al., 1988; Ruderman, 1983). In most cases, Items 1, 5, 6, 7, 8, and 9 load on the CD factor, and Items 2, 3, 4, and 10 load on the WF factor (Blanchard & Frost, 1983; Drewnowski et al., 1982; Ruderman, 1983). Two factors often account for 50% to 60% of the variance. Herman and Polivy (1975) originally found the correlation among the two factors to be .48, while the more recent studies found subscale correlations ranging from .17 to .62. Further evidence for the usual two-factor model was found by Allison et al. (1992), who performed orthogonal and oblique confirmatory factor analyses. The CD and WF factors accounted for 39% and 15% of the total variance, respectively. The original CD and WF scales correlated at .50. Boerner et al. (2004) used structure equation modeling to conduct a confirmatory factor analysis on the RS. To facilitate the analysis, they combined items into parcels for factors with four or more items. The sample included 215 female and 214 male college students. The results indicated that the standard two-factor structure was a less than optimal fit using the comparative fit index (CFI = .85) but a fair fit using the root mean square error of approximation (RMSEA = .08). Similarly, in a series of factor analyses by Klem, Klesges, and Shadish (1990) on a sample of 229 college students (117 men, 112 women), the traditional two-factor model was only a fair fit with the data. Occasionally, studies find more than two factors in the RS. Often, the results are attributed to the poor performance of certain specific items. van Strien et al. (2002) point out that there is generally poor consensus on the factorial assignment of Items 6 (splurging), 7 (thoughts about food), and 10 (history of overweight). The authors used maximum likelihood factor analysis to examine the RS responses from a sample of 209 female college students. The initial results suggested that a three-factor model fit the data the best, c2 (35) = 13.65, p = .75. After oblique rotation, most items had high loadings on the first factor (36% of the variance), but the items from the WF subscale (2, 3, 4, 10) had the highest loadings on this factor. The five items from the CD subscale (1, 5, 7, 8, 9) and one item from the WF subscale (10) loaded highly on the second factor (9% of the variance). All items loaded negatively on the third factor (only 3% of the variance). Item 6 loaded highly on the first and third factors. When a two-factor solution was examined, Items 1, 6, and 10 were observed to load highly on both factors. The authors repeated their analysis after eliminating Items 6 and 10 due to their failure to load reliably on a single factor. Item 1 was kept because it was “considered central to the concept of dietary concern.” The best-fit model included two factors, c2 (13) = 12.55, with Items 2, 3, and 4 loading on the first factor (WF; 33% of the variance) and Items 1, 5, 7, 8, and 9 loading on the second factor (CD; 14% of the variance). In a sample of 110 college students, Williams, Spencer, and Edelmann (1987) used principal components analysis to identify three factors with an eigenvalue greater than 1.4. The first factor included items primarily from the WF (1, 2 3, 4, 10) subscale, the second included items primarily from the CD subscale (5, 6, 8), and the third factor, labeled attention to food intake, included Items 2, 7, and 9. In this case, Item 2 loaded on the second and third factors. The three factors accounted for 27.7%, 21.4%, and 13.8% of the variance, respectively.


The findings of van Strien et al. (2002) and Williams et al. (1987) serve as a reminder that Herman and Polivy’s conceptualization of restraint, as measured by the RS, includes several aspects of eating and attitudes, behaviors, and personal history that are related, but not perfectly so. Researchers who intended to measure the construct of restrain as conceptualized by Herman and Polivy need to recognize that the heterogeneity of constructs being assessed may be problematic. Those who desire a more “pure” (i.e., unidimensional) measure restraint are encouraged to use the restraint subscale from the Three Factor Eating Questionnaire or the Dutch Eating Behavior Questionnaire. The developers of the RS intended it to be used as a single-factor measure (Polivy et al., 1988), and in most situations involving normal-weight samples, it should be used that way in primary analyses. Use of the total RS score will allow comparison with the majority of studies that have been conducted using the RS. However, the accumulated psychometric evidence suggests that the RS is multifactorial. van Strien et al. (2002) state that “use of total RS scores should be strongly discouraged” because the CD and WF subscales appear to measure qualitatively different constructs that may relate to outcomes such as disinhibited eating in different directions. Furthermore, the CD and WF subscales may interact in unpredictable ways. As such, it may often prove instructive to conduct secondary analyses that reanalyze data using the separate CD and WF subscales. If results replicate with one factor but not the other, it may provide valuable information about the source of the findings with the full scale.

Factorial Composition in Samples With a Significant Proportion of Overweight Participants The two-factor model of the RS does not appear to be as reliable in samples composed primarily of overweight or eating-disordered participants. Most often, these studies report three or more factors (W. G. Johnson, Corrigan, Crusco, & Schlundt, 1986; W. G. Johnson, Lake, & Mahan, 1983; Lowe, 1984; Ruderman, 1983). Oblique factor rotation on samples including large numbers of obese participants often finds that Items 6 and 7 load on a third factor, possibly related to overeating. For example, Ruderman (1983) identified a four-four factor solution in a sample of 58 obese college students with a principal components factor analysis with orthogonal rotation. The factors consisted of a Weight Fluctuation dimension (25% of the variance), a Binge dimension (17% of the variance), a Tendency to Diet dimension (15% of the variance), and an Overconcern With Dieting dimension (12% of the variance). In addition, Lowe’s (1984) exploratory principal components analysis found three factors with eigenvalues > 1.0. After oblique rotation, Items 1, 5, 8, 9, and 10 loaded on the first factor (29.3% of the variance), dubbed dietary concern and weight history. The second factor (28.3% of the variance), weight fluctuation, consisted of Items 2 to 4. Items 6 and 7 loaded on a third factor (17.6% of the variance). The greater the proportion of overweight people in a sample, the more factors emerge (Ruderman, 1986). This factor instability may be a sign of differential validity or the result of restricted variance due to homogeneity of the sample. When a sample is homogeneous, the correlation coefficients among items are reduced, leading to an increased likelihood of the identification of additional factors in a factor-analytic study.

Factor Stability A few studies have been conducted to test the factor stability of the RS. Blanchard and Frost (1983) found the factor structure of the RS to be stable across two samples of female college students. Tucker’s (1951) congruence coefficient (CC) was above .99 for both factors, indicating


excellent factor stability. Allison et al. (1992) found that the CC for the RS factors for males and females was over .95. For random splits of the sample, the CC was over .99. A comparison of obese and nonobese subjects produced a CC of .96 for the CD factor and .92 for the WF factor. Boerner et al. (2004) used the guidelines described by Hoyle and Smith (1994) to test the factor stability of the RS for a sample of college men (n = 214) and women (n = 215). The authors conclude that the RS is invariant across gender.

Construct Validity: Convergent and Discriminant Validity As opposed to other restraint scales that appear to measure actual dieting behaviors associated with caloric restriction (e.g., TFEQ, DEBQ), the RS appears to measure failed attempts at dieting (Heatherton et al., 1988). Researchers frequently consider the construct of restraint, as measured by the RS, to encompass both efforts at restricting food intake and episodes of overeating (van Strien, 1997). This conceptualization of restraint, as measured by the RS, was supported in analyses by van Strien et al. (2007), who used confirmatory factor analysis to examine the RS in relation to other measures of dieting, overeating, and body dissatisfaction in a sample of normal-weight (n = 349) and overweight (n = 409) females. A three-factor model was posited. The first factor, labeled overeating, consisted of the TFEQ disinhibition scale, the DEBQ emotional eating scale, DEBQ external eating scale, the Eating Disorder Inventory Revised (EDI-II) bulimic eating scale, and the question, “Have you ever had an eating binge, i.e., you ate an amount of food others would consider unusually large?” The second factor, labeled dieting, consisted of the DEBQ restraint scale, the TFEQ restraint scale, and the question, “Are you currently dieting?” The third factor, labeled body dissatisfaction, consisted of the EDI-II drive for thinness and body dissatisfaction scales. The confirmatory factor analyses were conducted at the level of scale scores rather than individual items. A model in which the RS loaded on all three factors was a better fit of the data than a model in which the RS loaded only on the dieting factor. The association of the RS with the overeating factor supports the conceptualization of the RS as a measure of unsuccessful dieting. Further support for the RS as a measure of unsuccessful dieting comes from a study by K. K. J. Ferguson, Brink, Wood, and Koop (1992), who studied the individual RS item responses of a group of overweight participants in a dieting program. A group of 41 female and 41 male successful dieters was identified, who lost at least 5% of their body weight and maintained the loss for a year with no more than 5 lbs. regain. Unsuccessful dieters, including 32 women and 28 men, failed to meet these benchmarks. Unsuccessful dieters were more likely than successful dieters to endorse items related to overeating and food obsession, such as, “Do you eat sensibly in front of others and splurge alone?” and “Do you give too much time and thought to food?” On the other hand, unsuccessful dieters were less likely to endorse items related to restriction of food intake, such as, “How conscious are you of what you are eating?” This study is partly consistent and partly inconsistent with what Herman and Polivy’s restraint theory would predict: Unsuccessful dieters were higher on disinhibiton items but lower on restriction items. According to Herman and Polivy, unsuccessful dieters should be higher on both because the continuing attempts to restrict presumably should be fueling the overeating.

Weight and Obesity Status Given that the RS is associated with both efforts at caloric restriction and a propensity toward overeating, it is not surprising that researchers have found a variety of relationships


with weight and obesity status. Researchers have studied the relationship between the RS and weight primarily by correlating RS scores with body weight and body mass index (BMI), comparing the weight and BMI of restrained and unrestrained eaters, and comparing RS scores among normal-weight and overweight participants. Drewnowski et al. (1982) found a relationship between only the WF subscale and percentage overweight. Drewnowski et al. also found that overweight participants scored higher than normal-weight participants on the total RS and the WF subscale but not the CD subscale. Because greater weight fluctuations in overweight individuals could stem from biological characteristics of adipose tissue per se (rather than from repeated periods of weight loss dieting and disinhibition-induced weight regain), Drewnowski et al. suggested that the RS may not be an appropriate measure of restrained eating in overweight individuals. However, Lowe (1984) found that CD (r = .41) but not WF (r = –.01) was related to overweight status in a sample of 217 college students (96 men, 118 women, 3 unknown). The discrepancy between the Lowe and Drewnowski et al. findings is likely the result of a greater proportion of overweight participants in the Drewnoswki sample. This interpretation is supported by Allison et al. (1992), who found that obese participants (n = 78) obtained significantly higher scores on the RS and the WF subscale but not CD. In two studies, Ruderman (1983, 1985) found correlations of .37 and .38 between RS scores and percentage overweight. In a study comparing overweight and nonoverweight participants, Klem, Klesges, Bene, and Mellon (1990) found that overweight participants obtained significantly higher scores on the CD and WF subscales, as well as on the total RS. In a sample of 358 adults (201 men and 157 women), de Castro (1995) found that higher RS scores were associated with higher body weights. Similarly, a Portuguese translation of the RS was significantly correlated with BMI in a sample of patients suffering from anorexia nervosa or bulimia nervosa (r = .38) and non-eating-disordered controls (r = .43; Scagliusi et al., 2005). Lowe (1984) found that restrained eaters had greater relative weights than unrestrained eaters, even though all participants were within the normal weight range. The RS failed to prospectively predict changes in body weight in three studies involving college students (Klesges, Klem, Epkins, & Klesges, 1991; Lowe et al., 2006; Tiggemann, 1994). However, Klesges et al. (1992) found that RS scores predicted weight gain among adult women but not men over a 1-year period when the relationship was analyzed in a multiple linear regression, including other physiological, demographic, and activity variables. Williamson et al. (2007) reported that RS scores increased during a weight loss intervention, but changes in RS were not correlated with relative energy balance during the diet. There appears to be a relationship between the RS and body weight. However, the relationship is not consistent across samples and may be artificially inflated among overweight and obese individuals. Given that nearly all literature on the RS has involved primarily normalweight individuals, that overweight restrained eaters and dieters do not behave like those of normal weight (Lowe et al., 1991; Ruderman, 1986), and that the RS has weaker psychometric properties in overweight individuals, the RS is not well suited as a measure of restrained eating in overweight samples.

Naturalistic Food Consumption Several authors have attempted to find a relationship between the RS and measures of naturalistic food consumption. However, most of these studies rely on self-reported dietary intake via food diaries, which have poor validity in general (Bandini, Schoeller, Dyr, & Dietz, 1990; Lichtman et al., 1992; Livingstone, Prentice, & Strain, 1990; Prentice et al., 1986), but especially


among overweight samples (Lichtman et al., 1992; Prentice et al., 1986) and restrained eaters (for a review, see Maurer et al., 2006). Both of these groups tend to underreport food intake to a significantly greater degree than unrestrained normal-weight individuals. Laessle, Tuschl, Kotthaus, and Pirke (1989) failed to find a correlation between RS (r = –.04) and mean caloric intake over a 7-day period in a sample of 60 normal-weight women. Similarly, de Castro (1995) found no relationship between total caloric intake and RS over a 7-day period in a sample of 201 male and 157 female adult participants. In a study by French et al. (1994), RS score was not related to caloric intake over a 6-month period, as measured by the Block Food Frequency Questionnaire (FFQ; Block et al., 1986). All three of these studies relied on selfreported intake. The fact that restrained eaters are more likely to underreport their actual food intake could be masking a tendency toward greater intake in restrained eaters. Consistent with this speculation are findings indicating that measures of restrained eating prospectively predict weight gain rather than weight loss (Stice et al., 2004).

Eating Disorders and Psychopathology The creators of the RS have suggested that dietary restraint and eating-disordered attitudes and behaviors are inherently related and have gone so far as to say that the type of dieting that is measured by the RS can lead to the development of eating disorders (Heatherton & Polivy, 1992; Polivy & Herman, 1985). A variety of cross-sectional studies support this claim. Ruderman and Grace (1987) found that the RS was correlated with the BULIT (Smith & Thelen, 1984), a measure of bulimia, in a sample of 108 women. The partial correlation between the BULIT and the CD subscale of the RS was still statistically significant when WF subscale scores were controlled. However, the relationship between WF and the BULIT was nonsignificant when the CD scores were controlled. In a sample of college students (Boerner et al., 2004), the RS total score was significantly correlated with the BULIT-R (Thelen, Farmer, Wonderlich, & Smith, 1991) among both men (r = .56, n = 214) and women (r = .69, n = 215). In addition, scores for both men (r = .46) and women (r = .64) were correlated with a measure of anorexic symptomatology, the Eating Attitudes Test (EAT; Garner & Garfinkel, 1979). Using a Portuguese translation of the RS, Scagliusi et al. (2005) found that bulimics (n = 24) scored significantly higher on the RS than anorexics (n = 15), who obtained significantly greater scores than non-eatingdisordered college students (n = 57). Prussin and Harvey (1991) compared a subsample of 38 individuals meeting DSM-III-R criteria for bulimia to 136 non-eating-disordered participants in a sample of normal-weight female runners. Bulimic participants had significantly higher RS scores. Bourne, Bryant, Griffiths, Touyz, and Beaumont (1998) found that the RS and its subscales were significantly correlated with greater frequency and intensity of disordered eating behaviors, as measured with the Eating Behavior Rating Scale (Wilson, Touyz, Dunn, & Beumont, 1989), during a video-recorded test meal. Griffiths et al. (2000) found significant relationships between the RS and abnormal eating attitudes and general dissatisfaction with one’s life in a sample of 82 college students. Prospective studies have confirmed that elevated RS scores predict the future onset of binge eating (Stice, Killen, Hayward, & Taylor, 1998) and bulimic pathology (Killen, Taylor, Hayward, & Wilson, 1994; Killen et al., 1996). In a sample of 967 adolescent girls who were followed over a 4-year period, Killen, Hayward, Wilson, and Taylor (1994) found that girls who developed bulimic symptoms had greater scores on both the CD and WF subscales of the RS at baseline compared to girls who remained asymptomatic. In a similar study of 543 female high


school students, Stice et al. (1998) reported that RS scores at baseline predicted onset of objective binge eating, subjective binge eating, and purging. Two items referring to binge eating were removed from the RS for this analysis because of concerns regarding criterion confounding, which are discussed below. Scores on the RS are clearly associated with measures of eating-disordered attitudes and behaviors. This is not surprising since dieting is a cardinal feature of both anorexia and bulimia nervosa, and overeating is a cardinal feature of bulimia nervosa. In addition, there is some evidence that RS scores are associated with depression and general dissatisfaction with life. However, Stice et al. (1997) suggest that the relationships observed between the RS and measures of eating-disordered symptomatology are the result of criterion confounding of the RS, which includes items related to disinhibited eating, a close relation of binge eating. When these items were removed (Items 6 and 8), the relationship between the RS and measures of disordered eating were significantly reduced among a sample of 117 female college students. The relationships were further weakened when items pertaining to weight fluctuation (which may create an artificial relationship between the RS and measures of eating-disordered symptomatology) were removed. The authors’ argument for criterion confounding of the RS is strengthened by the fact that the DEBQ-R, which does not included items related to weight fluctuation or disinhibited eating, did not show equivalent relationships with measures of disordered eating. Because the RS and other measures of restrained eating have been linked to the development of unhealthy eating behaviors, it is now widely accepted that “dieting” plays a causal role in the onset of eating disorders (e.g., Hawkins & Clement, 1984; Heatherton & Polivy, 1992; Polivy & Herman, 1985). In rare cases involving radical dieting and extensive weight loss to subnormal levels, there is reason to believe that such a connection exists (e.g., Butryn & Wadden, 2005). However, experimental evidence suggests that prescribed diets involving gradual weight loss reduce binge eating in normal-weight and overweight individuals (for a review, see Stice et al., 2004). This evidence, combined with studies indicating that restraint scales do not reflect hypocaloric dieting (Stice et al., 2007), seriously questions the prevalent assumption that garden-variety dieting helps cause eating disorders.

Susceptibility to Response Sets Historically, restrained eaters were thought to be motivated by a desire to attain a thin body to conform to socially defined standards for attractiveness (Polivy & Herman, 1987). Furthermore, some items on the RS, especially those related to overeating, may be embarrassing to endorse. Thus, it seems plausible that the RS may be influenced by social desirability bias, which is the inclination to present oneself in a manner that will be viewed favorably by others. Several researchers have tested this theory by correlating the RS with measures of social desirability responding. Most measures of social desirability responding present participants with a list of behaviors that are either socially desirable but infrequently practiced or frequently practiced but socially undesirable. Attempts to “fake good” are indicated by endorsement of the former type of behavior and denial of the latter type. The Minnesota Multiphasic Personality Inventory (MMPI) L, or “lie” scale, is possibly the most well-known measure of social desirability responding. The items comprising the Edwards Social Desirability Scale (Edwards, 1957), and some items from the Marlowe-Crowne Social Desirability Scale (MCSD; Crowne & Marlowe, 1964) were taken from the MMPI.


W. G. Johnson et al. (1983, 1986) found small and nonsignificant correlations between the RS, the MMPI Lie scale, and the MCSD for bulimics, obese nondieters, and “normals.” However, the relationship between the RS and the MMPI Lie scale (r = –.33), as well as the RS and MCSD (r = –.51), was moderate and negative for a sample of 27 obese dieters (W. G. Johnson et al., 1983). Ruderman (1983) found the opposite; the relationship between the RS and the Eysenck Lie Scale was stronger for nonobese participants (r = –.70) than obese participants (r = –.13). Other studies have found small and nonsignificant correlations between the RS and the Edwards Social Desirability Scale (Kickham & Gayton, 1977) and the RS and MCSD among normal-weight participants (Corrigan & Ekstrand, 1988; Ruderman, 1983) and obese participants (Ruderman, 1983). In a subset of participants (n = 73), Allison et al. (1992) found that the RS correlated with the MCSD (r = –.27) and the Edwards Social Desirability Scale (r = −.05). The authors also found that RS items that were rated as more desirable were endorsed more frequently. In the same study, when participants were instructed to “create the most favorable impression you can,” scores on the RS were low (mean = 8.75). When instructed to “create the worst possible impression,” the mean score was very high (mean = 30.65). Generally, the relationship between the RS and social desirability scales is negative, meaning that high scores on the RS are associated with relatively elevated endorsement of socially undesirable behavior. These findings present an interesting contrast to restraint theory, which suggests that restrained eaters’ behavior is motivated by a desire to attain a more socially desirable appearance. Regardless, the RS is transparent and can easily be “faked” good or bad. Finally, McCrae and Costa (1983a, 1983b) point out that correlations between a psychometric instrument and measures of social desirability responding should not necessarily be taken as a sign of invalidity of the instrument. It is generally undesirable to have a measure correlate with socially desirable motives, unless such a relationship can be argued to be part of the construct the measure is supposed to assess. In the case of the RS, the creators of the scale explicitly state that individuals who score highly on the measure are presumed to be highly influenced by socially dictated standards for appearance (Polivy & Herman, 1987).

Predictions of Laboratory Behavior The RS is well known for its ability to predict disinhibited eating in laboratory studies using the preload paradigm (Herman & Polivy, 1984; Lowe, 1993). In these studies, participants are typically designated as restrained or unrestrained eaters based on the median score of the RS. Half of each group will be assigned to consume a high-calorie preload, such as a milkshake, before they participate in a “taste test” of palatable food, such as ice cream. The outcome measure is the amount of food consumed during the taste test, which is surreptitiously monitored by the experimenter. Unrestrained eaters typically compensate for a preload by consuming fewer calories in the preload than in the no-preload condition. Restrained eaters show the opposite trend: They will show evidence of disinhibited eating and consume somewhat more after than in the absence of a preload. This pattern of findings is typically observed only when dietary restraint is measured with the RS but not other measures such as the TFEQ or DEBQ (Lowe, 1993). Notably, a caloric preload is not the only stimulus that will lead to disinhibited eating. Emotional distress (Herman & Polivy, 1980), threat of electric shock (Herman & Polivy, 1975), and increased cognitive load (Ward & Mann, 2000) also result in disinhibition. Furthermore, restrained eaters will exhibit disinhibited eating when they are led to believe that they have


consumed a high-calorie preload when in fact the preload they consumed was low in calories (e.g., Heatherton, Polivy, & Herman, 1989). Thus, disinhibited eating seems to occur when restrained eaters believe that their efforts at caloric restriction have been “blown” or when they are distracted from their efforts at restraint by an engrossing or distressing stimulus. The trend toward disregulation of food intake by restrained eaters was also observed in a study by Westerterp-Plantenga, Wouters, and ten Hoor (1991) in which 6 obese and 18 normal-weight women were served a four-course meal. Participants were allowed to eat as much as they wished during the second course, but the amount of food served during the other three courses was fixed. Eating behavior was observed, and the amount of food eaten was surreptitiously measured by a scale under the participant’s plate. Participants who were low on the RS scale showed a decreased rate of intake following the first course. Restrained women showed a pattern of progressive linear intake across the meal. This result may reflect the same process (lack of response to eating what is normally a satiating amount of food) as observed in preload studies, even though the indicator was different (rate of eating over the meal). The relationship between the RS and eating behavior observed in the laboratory is complex (Lowe, 1993). A sizable minority of studies have failed to find evidence of disinhibited eating in restrained eaters (e.g., Ouwens, van Strien, & van der Staak, 2003; van Strien, Cleven, & Schippers, 2000), while some have found that the effect of disinhibition is better accounted for by other constructs such as attributional style (Rotenberg & Flood, 2000). In addition, van Strien et al. (2002) found that the WF and CD subscales interacted with the preload in opposite directions in the prediction of food intake during the taste test, suggesting that the component parts of Herman and Polivy’s Restraint Scale may be differentially related to behavioral outcomes. Finally, as with other aspects of restrained eating, the outcome of laboratory studies seems partly dependent on the participants’ weights. van Strien et al. (2007) note that the disinhibition effect has never been observed in overweight restrained eaters. This observation reinforces the recommendation that the RS not be used in overweight samples. While some of the laboratory studies cited here seem to suggest that restrained eaters eat less than unrestrained eaters in the absence of a disinhibiting stimulus (Herman & Polivy, 1984), a series of studies by Stice and colleagues (Stice et al., 2004, 2007) strongly suggest that such laboratory-based findings of reduced eating by restrained eaters in the laboratory do not generalize to their food intake outside the laboratory.

Readability The reading level of the RS has been estimated to be between the fourth and ninth grades (Allison & Franklin, 1993).

Stunkard and Messick’s TFEQ-R Scale Description The Three Factor Eating Questionnaire (TFEQ), also known as the Eating Inventory (Stunkard & Messick, 1988), was created by Stunkard and Messick (1985) in response to a developing awareness of the limitations of the RS. The authors expressed concerns with


regard to the content of the RS and its construct validity. In regards to the content of the RS, the authors point out that, while the RS was not designed to measure the behavior of overweight and obese persons, its creators had suggested that the RS measured the construct of dieting as separate from the construct of overweight. Furthermore, they indicated that the cause of many behaviors associated with obesity was a history of dieting per se (Hibscher & Herman, 1977). However, it became increasingly apparent that the RS was indeed influenced by obesity. Some studies reported that overweight restrained eaters did not show evidence of disinhibited eating as did normal-weight restrained eaters. Furthermore, the RS contains items related to weight fluctuation that may artificially inflate the scale scores of persons suffering from overweight and obesity. Finally, the relationships that researchers reported for the RS and various outcome measures such as food consumption varied in strength and even direction, and the relationships seemed to vary by obesity status. Herman and Polivy’s hypothesis that restraint accounted for the eating behavior of obese individuals was not supported by reports that restrained obese individuals did not demonstrate counterregulatory eating (Ruderman, 1986). In response to these concerns, as well as the desire for a measure that would be more reliably related to food intake in normal-weight and obese persons, Stunkard (1981) and later Stunkard and Messick (1985) developed the restraint scale of the TFEQ (TFEQ-R). The first version of the TFEQ borrowed several items from the RS and Pudel et al.’s (1975) Latent Obesity Questionnaire, and 17 original items were also included. The variety of questions included in the scale reflects Stunkard and Messick’s intention to capture several facets of eating behavior, including but not limited to dietary restraint. The original 67-item scale was administered to a sample of 220 participants, including both genders and persons of both obese and normal weight. An exploratory factor analysis including all participants suggested three factors, representing behavioral restraint, lability in behavior and weight, and hunger. The results were essentially equivalent when separate factor analyses were conducted for men and women, as well as three groups of participants who were ostensibly low, medium, and high on restraint. On the basis of these preliminary results, the authors modified some items and added others in an effort to capture more accurately the constructs measured by each of the newly identified factors and to heighten the distinctiveness of each factor. A new sample, consisting of 53 (7 men and 46 women) participants in the same intensive weight loss program and 45 (5 men, 13 women, and 27 of indeterminate gender) completed a questionnaire comprising 93 items, including those that were unchanged, modified, and newly written. Of those, 58 items were selected for inclusion in the final version of the TFEQ. The items in the final measure were selected because of significant partial correlations with their provisional factors, while holding the other two subscales constant. Finally, the subscales were given new names: Cognitive Control of Eating (Factor I), Disinhibition (Factor II), and Susceptibility to Hunger (Factor III). Cronbach’s alpha was .92, .91, and .85 for Factors I, III, and III, respectively. A correlation of –.43 was found for Factors I and II, –.03 for Factors I and III, and .42 for Factors II and III. Although the scale was originally published as the Three-Factor Eating Questionnaire (Stunkard & Messick, 1985), it is now published by the Psychological Corporation as the Eating Inventory (Stunkard & Messick, 1988). For the purposes of the present chapter, we shall confine our discussion mainly to the Restraint Factor scale and shall refer to the restraint scale of the TFEQ as the TFEQ-R.


Sample As described in the previous section, a preliminary set of items was tested on a sample of 97 men and 123 women. The sample consisted of 78 “dieters” who were members of an intensive weight loss group, 62 nonobese “free eaters” who were selected by the dieters, and 80 persons who were chosen by the dieters for geographic proximity. The ages of the participants ranged from 17 to 77 years with a mean of 44. A second sample of 53 dieters (7 men and 46 women) and 45 free eaters (5 men, 13 women, and 27 of indeterminate gender) was used to refine the instrument. As before, the free eaters were nominated by the dieters, who were recruited from an intensive weight loss program. This second sample was used to identify the norms in the next section.

Norms Means, sample sizes, and standard deviations for participant groups on the TFEQ-R are presented in Table 5.4. As with other measures of restraint, studies often report lower TFEQ-R scores for men than women (e.g., Bellisle et al., 2004; de Castro, 1995). Stunkard and Messick (1988) suggest tentative TFEQ-R guidelines of 0 to 10 as “low average,” 11 to 13 as “high,” and 14 or more as “clinical range.” Care should be taken when attempting to classify persons into high- or low-restraint groups, as TFEQ-R scores differ by gender and nationality. Furthermore, scores should be interpreted in the context of the other characteristics of the responder. For example, a low TFEQ-R score in an obese person with obesity-related health problems may be a cause for concern, whereas a high restraint score in a thin woman could be problematic. It should also be noted that researchers sometimes change the dichotomized response format of the true/false items in the TFEQ-R to a 4-point response scale. This practice seems especially common in twin studies of the genetic component of eating behaviors (e.g., Neale, Mazzeo, & Bulik, 2003; Tholin, Rasmussen, Tynelius, & Karlson, 2005). While this practice may facilitate studies of heredity, the TFEQ-R scores reported in these studies are not directly comparable to studies using the standard scoring rubric.

Reliability Internal Consistency As can been seen in Table 5.2, Cronbach’s alpha for the TFEQ-R is routinely reported to be at or greater than .80. Unlike the RS, the TFEQ appears to be equally reliable for normal-weight and obese persons.

Test-Retest Stunkard and Messick (1985) cited an unpublished manuscript by Ganley that reported a test-retest correlation over a 1-month interval to be .93. Allison et al. (1992) found test-retest

162——HANDBOOK OF ASSESSMENT METHODS FOR EATING BEHAVIORS AND WEIGHT-RELATED PROBLEMS Table 5.4

Mean Three-Factor Eating Questionnaire–Restraint Scale (TFEQ-R) Scores Reported in the Literature

Participants

Author

Unrestrained eaters


62

6.0

5.5

Swedish control group

Bjorvell et al. (1986)a

58

9.8

4.2

Chilean university students

Lolas (1987)a

88

7.7

5.1

U.S. control sample

Ganley (1986)a

30

11.0

5.3

American adult men

French, Jeffery, and Wing (1994)

99

5.9

4.2

American adult women

French et al. (1994)

103

9.1

4.2

Postmenopausal American women

Hays, Bathalon, Robenoff, McCrory, and Roberts (2006)

36

10.6

6.9

36

9.0

5.5

46

7.8

4.1

At baseline At 4-year follow-up

n

Mean

SD

American adults


Japanese high school girls

Nogami (1986)a

243

5.6

3.7

Female White American college students

Atlas, Smith, Hohlstein, McCarthy, and Kroll (2002)

300

10.4

5.4

200

8.9

5.3

Female African American college students American college students

901

9.0

5.8

Females only


617

10.26

5.6

Males only

282

6.1

5.1

American male college students


214

4.7

4.7

American female college students


215

8.2

5.7

Australian female college students

Ricciardelli, Tate, and Williams (1997)

172

15.9

8.4

Japanese nursing students

Nogami (1986)a

270

6.3

3.6

German women


62

6.5

4.7

German women in a weight reduction program

Westenhoefer (1991)

46,132

13.1

4.3

German men in a weight reduction program

Westenhoefer (1991)

8,393

10.6

4.7

a. Reported in Stunkard and Messick (1988).


reliability to be .91 over a 2-week span. Bond, McDowell, and Wilkinson (2001) reported a testretest coefficient of .81 over 1 year.

Validity Content Validity Factorial Composition. While the focus of this chapter is measures of restraint, findings involving the other two TFEQ subscales are reviewed below because they can help shed light on the domain assessed by the TFEQ-R. Factor analyses of the full TFEQ, including items from all three subscales, typically find that a three-factor solution fits the data well. Stunkard and Messick (1985) conducted several factor analyses during development of the measure, with the express intention of creating distinct subscales. Little variation in the factor structure was found between dieters in a weight loss program who were ostensibly restrained eaters and neighbors of the dieters who were ostensibly moderately restrained. However, the factor structure for a group of “free eaters” was slightly less simple, possibly because of infrequent endorsement of items related to restraint and disinhibition. Regardless, the restraint factor (Factor I) was robust across all groups. Highly similar results were obtained by Hyland, Irvine, Thacker, and Dan (1989) and Ganley (1988). Boerner et al. (2004) used structural equation modeling to conduct a confirmatory factor analysis of several measures of eating attitudes and behaviors simultaneously. Items from the subscales of each measure were combined into item parcels to facilitate analysis. The authors found that the typical three-factor model fit the TFEQ very well. Similar results were obtained by Atlas, Smith, Hohlstein, McCarthy, and Kroll (2002). In contrast, Mazzeo, Aggen, Anderson, Tozzi, and Bulik (2003) tested three models of the TFEQ using two types of confirmatory factor analysis and found that none of the models produced an acceptable fit of the data. However, the authors used a modified TFEQ that excluded 15 items and altered the response option for some other items. It is unclear to what degree the results reported in this study may have been affected by Mazzeo et al.’s manipulation of the TFEQ. Of greater relevance to the study of restrained eating are studies that focus more specifically on the 21 items of the TFEQ-R. Ricciardelli and Williams (1997) examined the factor structure of the TFEQ-R. The sample consisted of 144 female college students. A principal components analysis with varimax rotation identified three factors. The first factor, accounting for 33.5% of the variance, included six items and was labeled emotional/cognitive concerns for dieting. The second factor contained seven items, accounted for 7.8% of the variance, and was labeled calorie knowledge. The third factor was made up of five items, accounting for 6.6% of the variance, and was labeled behavioral dieting control. Three items failed to load on any of the factors. Ricciardelli and Williams suggested that Factors I and III are similar to the constructs of cognitive restraint and behavioral restraint that have been identified in the literature on problem drinking. They conclude that Factor III may be a better measure of successful dieting than the total TFEQ-R, as Factor III was negatively correlated with BMI. Westenhoefer (1991) identified two highly correlated sources of variance in the TFEQ-R using a variant of discriminant analysis. In a sample of 46,132 female and 8,393 male Germans in a weight loss program, factors were identified representing “Flexible” control and “Rigid”


control over eating. Persons scoring highly on the rigid control scale were characterized by a dichotomized, “all-or-nothing” approach to eating. They reported dieting frequently but did not seem to follow any specific plan. On the other hand, individuals scoring highly on flexible control reported eating more slowly, taking smaller helpings, and controlling their eating by using situation-specific guidelines rather than inflexible rules. Rigid control was associated with high disinhibition, whereas flexible control was linked to low disinhibition. Allison et al. (1992) conducted a principal components factor analysis on the TFEQ-R responses of 901 college students. While the Minimum Average Partial (MAP) test (Zwick & Velicer, 1986) suggested a one-factor solution, and goodness-of-fit indices were good to fair for this model, a two-factor solution similar to that found by Westenhoefer (1991) was eventually retained. Catell’s scree test and the Guttman-Kaiser eigenvalues > 1 rule each suggested a two-factor solution. Varimax rotation was attempted but later abandoned when an oblique rotation yielded a simpler factor pattern. The two factors seemed to represent a cognitive dimension (35% of the variance) and a behavioral dimension (6% of the variance) of restraint. However, the correlation between the factors was high (r = .56). The authors concluded that the TFEQ-R contains two highly correlated primary factors that can be considered nested within a broader secondary factor. Gorman et al. (1993) conducted a further analysis of the findings reported in Allison et al. (1992). The high correlation between the two factors and the substantially greater endorsement of items in the cognitive restraint factor as compared to the behavior restraint factor led the authors to consider alternative methods of analyzing the data. Psychometric research has shown that conventional linear factor analysis techniques will often produce spurious factors when items differ considerably in their endorsement rates (G. A. Ferguson, 1941; Gibson, 1967; Horst, 1965; McDonald & Ahlawat, 1974). Thus, Gorman et al. reanalyzed the data using nonlinear techniques, including multidimensional scaling and Rasch model scaling (Hambleton, Swaminathan, & Rogers, 1991), that alleviate the biases of traditional methods. The results suggested that the TFEQ-R items form a continuum that begins with relatively common thoughts of reducing eating and ends with overt, deliberate, but relatively rare actions to reduce eating. Taken together, these findings suggest that the TFEQ-R performs well as a unidimensional measure of restrained eating but that it can also be further bifurcated into a cognitive and a behavioral component. There is evidence that these two components may form a continuum ranging from typical thoughts of reducing intake to actual behaviors at limiting consumption that are rarely followed through with. While further research involving nonlinear analytic techniques is needed to strengthen this conceptualization of the TFEQ-R, it appears that these results dovetail nicely with recent data suggesting that restrained eaters on the TFEQ-R do not actually reduce their food intake below their energy needs, even though they may wish they could do so (Stice et al., 2004, 2007).

Factor Stability Allison et al. (1992) found that Tucker’s CC was high for random splits of the subject sample (CC > .97) but only modest (CC < .90) when comparing obese and normal-weight participants and low when comparing across gender (CC < .90). However, Boerner et al. (2004) found that the TFEQ-R was invariant across gender using the steps described by Hoyle and Smith (1994) for testing measurement invariance. Atlas et al. (2002) found that the TFEQ-R performed equally well for African Americans as Whites. More research is needed to compare the performance of the TFEQ-R in obese and normal-weight participants.


Construct Validity: Convergent and Divergent Validity Relationships Among the TFEQ Subscales Stunkard and Messick intended for the subscales of the TFEQ to be conceptually and empirically distinct. For the most part, this goal seems to have been accomplished, although there is notable overlap between the TFEQ-R and the other subscales, in some reports. For example, Atlas et al. (2002) found a moderately strong correlation between the TFEQ-R and the TFEQ Hunger subscale for both White (r = .74) and African American (r = .77) women. However, the correlation between the TFEQ-R and the TFEQ Disinhibition subscale was substantially stronger for White (r = .47) than African American (r = .05) women. Despite the correlations that have been observed in such studies, the TFEQ subscales were never intended to be combined into a single “total” score, and there is no evidence that such an amalgam has any theoretical or empirical utility. The TFEQ subscales appear to relate to each other differently for obese and normal-weight individuals but similarly across gender. Bellisle et al. (2004) studied these relationships in a sample of 2,509 adults of both genders and varying weights. While correlations between the TFEQR and the Disinhibition and Hunger subscales were positive in the lowest BMI groups (i.e., BMI < 27), the relationship became increasingly more negative as BMI increased. In persons with BMI greater than 45, TFEQ-R was moderately negatively correlated with the Disinhibition subscale in women and men. In the same BMI category, the relationship between TFEQ-R and Hunger was r = –.30 for women and r = –.12 for men. Similar results were found by Foster et al. (1998), who reported moderately negative correlations between TFEQ-R and Disinhibition, as well as between TFEQ-R and Hunger, among overweight women seeking behavioral treatment for weight loss. In a sample of U.S. college students, Boerner et al. (2004) found that the TFEQ-R and Disinhibition subscale was moderately positively correlated among men and women. The correlation between TFEQ-R and Hunger was very weak for men and women. Similarly, in two samples of Dutch female college students, TFEQ-R was correlated with Disinhibition at r = .36 and r = .42 (Ouwens et al., 2003; van Strien et al., 2000, respectively). In a study by van Strien et al. (2007), a significant difference was observed in the correlation between TFEQ-R and Disinhibition for normal-weight (r = .41) and overweight (r = .07) subsamples. For people in the normal weight range, it may be that people with low Disinhibition or Hunger scores have very low risk for weight gain (they may be “naturally thin”), whereas those with higher scores may attempt to counter their chronic vulnerability to overeating and weight gain by being more restrained. Among those already obese, most may already be frequently overeating relative to their normal-weight peers, but those who are currently restraining their eating are (at least temporarily) reducing their vulnerability to this overeating.

Weight and Obesity Status During the measure development process, Stunkard and Messick (1985) found a correlation of .20 between restraint and weight. Since then, a variety of relationships have been reported. Allison et al. (1992) found no significant differences between obese and nonobese participants on the TFEQ-R. Ricciardelli and Williams (1997) reported that the TFEQ-R correlated with BMI (r = .25), previous dieting (r = .64), and current dieting (r = .65) in a sample of female college


students. Beiseigel and Nickols-Richardson (2004) found that a subgroup of normal-weight college women with high scores on the TFEQ-R possessed more fat mass (as measured by dual-energy X-ray absorptiometry) and had a higher body fat percentage than a subgroup of women with low restraint scores. When a French translation of the TFEQ-R was administered to 1,554 participants, 955 of whom were in the obese range, the TFEQ-R scale was positively associated with BMI in men but not in women (Bellisle et al., 2004). Obese and nononbese women did not differ significantly on the TFEQ-R. Furthermore, being obese as a child and/or adolescent was generally associated with more intense restraint, disinhibition, and hunger in adults, whether or not the subject was still obese at the time of the test. The authors conclude that some level of restraint may allow some children to grow out of obesity. This study was conducted with obese persons and their first-degree relatives, so the results may not be generalizable to persons with no family history of obesity. De Lauzon-Guillain et al. (2006) studied the relationship between eating behavior and weight gain in a community sample of 466 adults and 271 adolescents over a 2-year period in France. At baseline, a French translation of the TFEQ-R was positively associated with BMI in normal-weight participants but not overweight adults. While TFEQ-R scores did not predict changes in adiposity, a higher initial BMI was associated with a larger increase in TFEQ-R. Similarly, Hays, Bathalon, Roubenoff, McCrory, and Roberts (2006) examined predictors of weight change in a sample of 36 nonobese postmenopausal women in a 4-year longitudinal study. Hunger was the only TFEQ subscale that predicted weight gain. While the previous studies found either a positive relationship or no relationship between TFEQ-R and body size, Westenhoefer, Stunkard, and Pudel (1999) found that the TFEQ-R was negatively associated with BMI in both male and female Germans in a computer-assisted weight loss program. TFEQ-R was also positively associated with successful weight loss. Although not discussed by the authors, there were also apparently significant interactions between TFEQ-R and Disinhibition, such that the antiobesity effects of restraint were stronger at higher levels of disinhibition. This pattern of results was also observed by Williamson et al. (1995). These results are consistent with the previously mentioned argument that dietary restraint may be a desirable characteristic in already overweight individuals. Westenhoefer et al. (1999) further parsed their results by the flexible and rigid control subscales developed by Westenhoefer (1991). These analyses revealed that rigid control is associated with increased Disinhibition and higher BMI, whereas flexible control is associated with lower Disinhibition and lower BMI. Furthermore, successful weight losers had more flexible control at the beginning of the program and increased their flexible control scores during the program, whereas less successful participants had lower scores at the beginning and did not increase them during the program. Differences for rigid control, while statistically significant, were considerably smaller. The authors conclude that flexible control, but not rigid control, is associated with successful weight reduction. However, just as the potential causal association between restraint and overeating is open to debate (e.g., overeating may increase restraint, not vice versa), so is the causal status of rigid and flexible dieting. It is possible that flexible dieters are able to be flexible because their overeating tendencies are not as severe, whereas rigid dieters have learned that they can only control their eating by employing more definitive dieting rules. Generally, the TFEQ-R seems to be linked with successful weight loss. In addition to the studies described previously, Foster et al. (1998) found that weight loss treatment was associated with significant increases in restraint and decreases in disinhibition and hunger. Before treatment,


higher restraint scores were associated with lower body weights, and greater increases in restraint were correlated with greater weight losses. In a study of 46 adults (26 men and 20 women) seeking weight loss treatment, TFEQ-R scores increased significantly in treatment groups but not the control group (Williamson et al., 2007). Notably, of several measures of dietary restraint, the TFEQ-R was the only measure to be correlated with energy balance (as measured by a combination of doubly labeled water and change in body composition). However, it was the change in TFEQ-R, not its absolute value, that was associated with energy balance. Increases in TFEQ-R were associated with an energy deficit. Very little or no change in TFEQ-R was associated with energy excess. TFEQ-R is also related to weight maintenance. Westerterp-Plantenga, Kempen, and Saris (1998) found that participants who successfully maintained weight loss following a very lowcalorie diet experienced greater increases in TFEQ-R during the diet, as compared to participants with poorer weight maintenance, who did not experience as great an increase in TFEQ-R while dieting. TFEQ-R scales have also been linked to the construct of weight suppression (i.e., the difference between current and highest ever weight). de Castro (1995) reported an interaction between TFEQ-R and gender in the prediction of weight suppression in a sample of 201 male and 157 female adults. When participants were trichotomized based on their TFEQ-R scores, the current weights of high-restraint men were 10.5% below their highest weights, whereas the current weights of the moderate- and low-restraint groups were closer to their highest weights (5.2% and 6.6% below their highest weights, respectively). This pattern was not observed for women, who were 6.9% below their highest ever weight in all three restraint groups.

Naturalistic Food Consumption de Castro (1995) reported that highly restrained eaters had significantly lower self-reported caloric intake than dieters with low restraint. The differences resulted from significantly lower intakes of fat and carbohydrate in restrained eaters (although the usual cautions about underreporting in restrained eaters apply). In addition, overall daily intakes were less variable with higher levels of restraint. Participants high in restraint had lower deprivation ratios but not satiety ratios. This suggests that highly restrained participants ate significantly less than unrestrained eaters relative to their period of premeal deprivation than did the less restrained subjects, but there was no differential effect of meal size on time to next meal. In a study of food intake and physical activity, French et al. (1994) found that women who scored highly on the TFEQ-R reported significantly lower caloric intake, lower percent calories from sweets, and less frequent sweets consumption than women with low TFEQ-R scores. Men with high TFEQ-R scores reported a significantly greater percentage of calorie intake from protein and carbohydrate and less frequent consumption of beef, pork, whole milk, and sweets. Lahteenmaki and Tuorila (1995) studied the relationship between the TFEQ-R and the desired use and liking of a variety of foods in a sample of 253 women and 11 men attending Weight Watchers in Finland. The TFEQ-R was negatively related to the reported use of some food groups such as fruit-based sweet foods, butter, margarine, and regular-fat cheese but not to their desired use or liking. Beiseigel and Nickols-Richardson (2004) found that college women who score highly on the TFEQ-R consumed more servings of fruits and vegetables per day compared to women in a low-restraint group. Care must be taken when drawing inferences from studies linking the TFEQ-R to lower caloric intake and/or healthier intake (e.g., fewer fats/sweets, more fruits and vegetables) as restrained


eaters are known to underestimate their caloric intake to a greater degree than restrained eaters (for a review, see Maurer et al., 2006). Furthermore, the source of the underreporting seems to be disproportionately accounted for by the unhealthiest foods (Maurer et al., 2006).

Eating Disorders and Psychopathology A plethora of studies report cross-sectional correlations for the TFEQ-R and measures of eating disorders. For example, Boerner et al. (2004) found a correlation of .43 for men and .52 for women between the TFEQ-R and the Bulimia Test–Revised (BULIT-R; Thelen et al., 1991). Similarly, the correlation between the TFEQ-R and the EAT (Garner & Garfinkel, 1979) was .45 for men and .64 for women. Atlas et al. (2002) found that the TFEQ-R correlated with the BULIT-R at .47 for White and .69 for African American college women. Ricciardelli, Tate, and Williams (1997) found evidence that body dissatisfaction may mediate the relationship between the TFEQ-R and the BULIT-R. However, their conclusions are limited by the crosssectional nature of their research design. Rigid and flexible (Westenhoefer, 1991) control over eating appears to be differentially related to measures of eating disorders. In a field survey of 1,838 West Germans, rigid control was associated with more frequent and more severe binge episodes, whereas flexible control was associated with the opposite (Westenhoefer et al., 1999). The TFEQ-R as a whole was not related to binge frequency or severity. High scores on the TFEQ-R were associated with greater risk for using purging behaviors such as diuretics, laxatives, appetite suppressants, vomiting, physical exercise, and bodybuilding. Higher rigid control was associated with a higher risk of using all of these purging techniques except physical exercise and bodybuilding. Higher flexible control was associated with a lower risk of using diuretics or appetite suppressants and a higher likelihood of using physical exercise or bodybuilding as methods of weight control. Despite the correlations between the TFEQ-R and measures of eating-disordered attitudes and behaviors, Safer, Agras, Lowe, and Bryson (2004) reported that TFEQ-R scores did not decrease significantly during cognitive-behavioral therapy for bulimia in a sample of 134 women. Correlations between the TFEQ-R and measures of eating-disordered symptomatology should not be interpreted as supporting a causal link between this measure of dieting and eating disorders. For one, the studies finding such a relationship were all done with nonclinical populations, and only a very small percentage was likely to suffer from an eating disorder. Also, if there were a causal link, then those bulimic individuals who are actually dieting to try to lose weight should show particularly high levels of binge eating. Instead, strict dieting is associated with reduced, rather than enhanced, binge-eating frequency (Lowe et al., 1998, 2007). Finally, the observation that TFEQ-R scores do not decrease during treatment (Safer et al., 2004) for bulimia seems to suggest that the construct of dieing tapped by the TFEQ-R is not an important factor in the maintenance of this eating disorder. Prospective studies are needed to determine what, if any, role this type of dieting may play in the development and maintenance of disordered eating.

Susceptibility to Response Sets Allison et al. (1992) found weak correlations between the TFEQ-R and the Edwards and Marlowe-Crowne Social Desirability Scales (r = .05 and –.21, respectively). Furthermore, ratings of the social desirability of each item did not correlate with the frequency with which they were


endorsed. Finally, instructions to “fake good” and “fake bad” did not result in significantly different means on the TFEQ-R. On the basis of these results, the authors conclude that the TFEQ-R is not unduly influenced by socially desirable responding.

Predictions of Laboratory Behavior One of the most well-known qualities of Herman and Polivy’s Restraint Scale is its ability to predict disinhibited eating in the laboratory setting. In contrast, the TFEQ-R is not typically linked to disinhibited eating in preload/taste test studies (Lowe & Maycock, 1988; Rogers & Hill, 1989; Tuschl, Laessle, Platte, & Pirke, 1990; Westerterp, Nicolson, Boots, Mordant, & Westerterp, 1988; Westerterp-Plantenga et al., 1991). It is more common to find that a tendency toward disinhibited eating, as measured by the Disinhibition subscale of the TFEQ, for example, is a better predictor of overeating (e.g., Ouwens et al., 2003; van Strien et al., 2000). The discrepancy between the RS and the TFEQ-R in the prediction of disinhibited eating often has been explained by the assertion that the TFEQ-R tends to select a broad range of dieters, including those who are successful and unsuccessful, whereas the RS tends to select primarily failed dieters who have a tendency toward overeating (for a review, see van Strien, 1999). Thus, van Strien (1999) recommended that the TFEQ-R be used in conjunction with the TFEQ Disinhibition subscale to independently study the individual and combined associations of these constructs with eating behavior.

Readability The reading level of the TFEQ-R has been estimated to be between the sixth and ninth grades (Allison & Franklin, 1993).

Availability The TFEQ can be purchased from Harcourt Assessment (harcourtassessment.com).

Dutch Eating Behavior Questionnaire Description van Strien, Frijters, Bergers, et al. (1986) created the Dutch Eating Behavior Questionnaire (DEBQ) to facilitate research on the development and maintenance of human obesity. The measure was created partly in response to psychosomatic theory, externality theory, and Herman and Polivy’s restraint theory, all of which suggest that obesity is attributable to overeating. The DEBQ was created in response to the same criticisms of the RS that led Stunkard and Messick to develop the TFEQ. While the TFEQ was published before the DEBQ, the two measures were under development at about the same time. In fact, both scales borrowed items from Pudel’s et al.’s (1975) Latent Obesity Questionnaire, which may partially explain any correlation observed between the DEBQ and TFEQ restraint scales. In addition to a restraint subscale that


was intended to be distinct from measures of overeating and independent of obesity status, the DEBQ includes subscales for emotional eating and external eating. The restraint subscale includes items pertaining to deliberate, planned weight control. The emotional eating subscale prompts individuals to indicate how often they experience a desire to eat as a result of unpleasant emotions such as anxiety, sadness, and boredom. The external eating subscale has items that refer to increased consumption or desire for food in the presence of food-related stimuli. During the initial measure development process of the DEBQ, a pool of 100 items taken from previous measures, including the Eating Patterns Questionnaire and the Eating Behavior Inventory (O’Neil et al., 1979), were administered to a sample of 140 participants, including normal-weight and obese individuals. A series of factor analyses and item analyses were used to identify items that appeared factorially simple (i.e., tended to load only on one factor). In addition, some items were revised, and new items created, to increase the distinctiveness of the subscales. The final scale consisted of 33 items divided among three subscales. The response options for each item are on a Likert-type scale with the following categories: never (1), seldom (2), sometimes (3), often (4), and very often (5). The subscales of the DEBQ are typically scored by calculating the average response for all items in each scale. Although the developers’ intention was to create a measure with three distinct factors, a fourth factor was identified during the final analyses that represented emotional eating while bored. This fourth factor was not included as a formal subscale, as it contained items that loaded highly on other subscales, and was not of specific theoretical interest. For our purposes, all further discussion will be limited to the restraint subscale (DEBQ-R) of the DEBQ.

Sample The final form of the DEBQ was tested on a sample of 517 male and 653 female participants, 114 of whom were obese.

Norms Table 5.5 presents norms for the DEBQ restraint scale. Women appear to score higher on the DEBQ-R than men, and obese individuals seem to have higher scores than persons of normal weight. Care should be taken when classifying individuals as restrained and unrestrained as no empirically validated cutoff exists, and the distribution of scores varies by nationality. Although sample medians are often used to create two restraint groups, it is generally preferable to treat the DEBQ-R score (or any restraint score) as continuous when possible.

Reliability Internal Consistency The rigorous development process of the DEBQ resulted in a restraint factor with high internal consistency. As can be seen in Table 5.2, Cronbach’s alpha is generally greater than .90. Furthermore, the scale appears to be equally reliable in normal-weight and obese individuals.


Mean Dutch Eating Behavior Questionnaire–Restraint Subscale (DEBQ-R) Scores Reported in the Literature

Participants

Author

n

Mean

SD

Dutch adults

van Strien, Frijters, Bergers, and Defares (1986)

1169

2.2

0.9

498

1.8

0.8

71

2.3

0.8

Nonobese men only

427

1.8

0.7

Women only

642

2.5

0.9

73

3.0

0.8

569

2.4

0.9

Men only Obese men only

Obese women only Nonobese women only Dutch college students

Ouwens, van Strien, and van der Staak (2003)

209

2.6

0.9

Dutch college students


200

2.6

0.8

Normal-weight female Dutch college students


349

2.6

0.8

Overweight, nonobese Dutch women


409

3.2

0.7



901

2.9

1.0

281

2.3

0.9

7

3.1

0.8

Nonobese men only

274

2.3

0.0

Women only

607

3.1

1.0

Men only Obese men only

Obese women only Nonobese women only

23

3.2

0.8

584

3.1

1.0

393

2.7

0.8

Australian Grade 9 female adolescents

Banasiak, Wertheim, Koerner, and Voudouris (2001)

English men

Wardle (1986)

45

1.9

0.8

English women

Wardle (1986)

102

2.7

0.0

German women


60

2.4

0.6


Test-Retest In a sample of 165 adolescent girls, Banasiak, Wertheim, Koerner, and Voudouris (2001) found the test-retest reliability of the DEBQ-R to be .85 after a delay of 4 to 5 weeks. The retest coefficient for a 2-week span was .92.

Validity Factorial Composition Few published studies have tested the factor structure of the DEBQ. Of those that have, the majority found that a simple three-factor solution including all 33 items fits the data quite well, with a restraint factor that is clearly separate from the factors representing emotional eating and external eating (van Strien, Frijters, Bergers, et al.,1986; Wardle, 1987). van Strien, Frijters, Bergers, et al. (1986) also found the factor structure to be invariant for both genders and persons of obese and normal weight. Two other studies investigated the factor structure of the 10-item DEBQ restraint scale. After completing both exploratory and confirmatory factor analyses, Allison et al. (1992) concluded that the DEBQ-R was best described by a unifactorial solution accounting for 68% of the variance. However, Ogden (1993) observed that the DEBQ-R contains two potentially confounded aspects of dietary restraint: attempts at food restriction and actual restrictive behavior. To examine this possibility, she conducted an exploratory factor analysis of a modified DEBQ-R in which extra items were added to questions, including the word try, that specifically distinguished between intended restraint and successful restraint. In addition, two new items were added: “Do you attempt to diet in order to lose weight?” and “Do you regard yourself as a successful dieter?” All items but Item 4 loaded on a single factor containing the two additional items, which suggests that individuals do not distinguish between attempts at restraint and actual restraint behaviors. However, the possibility remains that restrained eating varies on a single continuum ranging from intentions to diet to actual restrictive behaviors, as was found in studies of the TFEQ-R by Gorman et al. (1993) and Allison et al. (1992).

Factor Stability During the measure development process, van Strien, Frijters, Bergers, et al. (1986) noted that the pattern of item-total scale correlations was similar for obese and normal-weight participants. Allison et al. (1992) conducted separate factor analyses of the DEBQ-R for obese and normal-weight participants, for men and women, and for random splits of the sample. They found that Tucker’s congruence coefficients were at least .990 in each split. Based on these data, the factor stability of the DEBQ-R seems excellent.

Construct Validity: Convergent and Discriminant Validity Preliminary evidence suggests that the restraint subscale of the DEBQ is minimally related to the other two DEBQ subscales. van Strien, Frijters, Bergers, et al. (1986) report that the DEBQ restraint scale correlated at .37 with the DEBQ emotional eating scale and .16 with the DEBQ external eating subscale in a mixed sample of normal-weight and obese individuals.


Weight and Obesity Status The mean DEBQ-R scores of 76 friendship cliques consisting of 523 adolescent girls were correlated with mean clique BMI (r = .38; Paxton, Schutz, Wertheim, & Muir, 1999). In a randomized controlled trial of behavioral weight loss interventions, DEBQ-R scores increased significantly in the three treatment conditions but not in a control condition (Williamson et al., 2007). The sample consisted of 46 overweight (25 < BMI < 30 kg/m2) individuals. Ogden (1993) studied a sample of “successful,” “reasonable,” and “failed” dieters, who were categorized based on whether they rated their success at dieting as higher, equivalent, or lower than their attempts at dieting, respectively. DEBQ-R scores were highest among the failed dieters, lowest among the successful dieters, and intermediate among the reasonable dieters. While this finding suggests that the DEBQ-R is related to unsuccessful attempts at dieting, care must be taken when interpreting the results, as there is no assessment of the reliability or validity of the self-reported measures of dieting frequency or success used in this study.

Naturalistic Food Consumption Several studies have reported moderate negative correlations between caloric intake and the DEBQ-R. In a sample of 50 female undergraduates and university staff, Wardle and Beales (1987) found a correlation of –.28 between the DEBQ-R and caloric intake over a 1-day period, as assessed by interviewers trained in conducting 24-hour food recalls. Similarly, in a sample of 110 Dutch women, van Strien, Frijters, Staveren, Defares, and Deurenberg (1986) reported a correlation of –.47 between the DEBQ-R and a measure of deviation from required energy intake, which was computed by subtracting the mean caloric intake across three 24-hour food recalls from an estimate of the number of calories needed for weight maintenance. This finding suggests that individuals who score high on the DEBQ-R consume fewer calories than what is needed to sustain their current body weight. Some of this difference may be the result of ingesting fewer high-calorie foods, as the DEBQ-R also correlated at –.28 with fat intake and –.38 with sugar intake. Laessle et al. (1989) also found that the DEBQ-R correlated at –.49 with a measure of caloric intake based on computer-assisted analysis of 7-day food diaries that were completed by 60 normal-weight women. Collectively, these studies seem to indicate that the DEBQ-R identifies individuals with comparatively lower food intake, which may result in negative energy balance. However, this conclusion is qualified by previously mentioned research that finds restrained eaters systematically underreport their food intake to a greater degree than unrestrained eaters and that the source of the underreporting is disproportionately accounted for by the unhealthiest foods (Stice et al., 2004, 2007).

Prediction of Laboratory Behavior Unlike the Restraint Scale, higher scores on the DEBQ-R are not typically associated with disinhibited eating behavior in preload studies. Of the studies that failed to detect disinhibited eating following a preload, two studies found a small but significant positive relationship between the DEBQ-R and food consumption during the “taste test” (van Strien et al., 2000; Wardle & Beales, 1987), while one other did not (Ouwens et al., 2003). Despite the lack of a disinhibition effect, participants scoring high on the DEBQ-R have been known to exhibit increased food consumption following a cognitive task (Lattimore & Caswell, 2004; Wallis & Hetherington, 2004) and a task involving ego threat (Wallis & Hetherington, 2004). In addition, female


restrained eaters (as identified by a median split of DEBQ-R scores) tended to consume more calories than unrestrained eaters, when given ad libitum access to large amounts of palatable food (Jansen, 1996). Notably, unrestrained eaters were able to estimate their caloric intake quite well, while restrained eaters underestimated their intake.

Disordered Eating and Psychopathology Like other measures of dietary restraint, the DEBQ-R is often correlated with eating-disordered attitudes and behaviors, as well as general measures of psychopathology. In a sample of 123 young adults, DEBQ-R was significantly associated with a measure of anxiety, but only for women (Jeffery & French, 1999). DEBQ-R was not associated with depression in either gender. Paxton et al. (1999) studied restraint and disordered eating in 79 friendship cliques consisting of 523 adolescent girls. The DEBQ-R was significantly correlated with mean clique scores for body image concerns and extreme weight loss behavior but not depression, self-esteem, or anxiety. Stice et al. (1997) reported correlations of .62, .53, and .69 between the DEBQ-R and the BULIT-R total score, the BULIT-R binge control subscale, and the bulimia factor of the EAT, respectively, among 117 female college students. However, some of the relationship between the DEBQ-R and measures of psychopathology may be explained by other variables. For example, in a study of 1,177 adolescent girls over a 1-year period, F. Johnson and Wardle (2005) found that the cross-sectional and prospective relationships between the DEBQ-R and symptoms of bulimia, low self-esteem, and depression were better accounted for by body dissatisfaction. The presence and later development of abnormal eating attitudes was the only outcome with which restraint was independently associated.

Susceptibility to Response Sets The DEBQ-R does not appear to be unduly influenced by social desirability responding or dissimulation. The correlation between the DEBQ-R and social desirability scales such as the Marlowe-Crowne Social Desirability Scale (r = –.08) and the Edwards Social Desirability Scale (r = –.24) appears to be weak and statistically nonsignificant (correlation coefficients from Allison et al., 1992; also see Corrigan & Ekstrand, 1988; van Strien, Frijters, Roosen, KnuimanHijl, & Defares, 1985). When each item of the DEBQ-R was rated for its social desirability, Allison et al. (1992) found that the social desirability ratings correlated with item endorsement at .67, indicating that the more desirable items were endorsed more frequently. When participants were instructed to “fake good” or “fake bad,” the resulting mean DEBQ-R scores were not significantly lower or higher than when such instructions were not given. These findings indicate that the DEBQ-R scale has good discriminant validity.

Readability The reading level of the TFEQ-R has been estimated to be between the fifth and eighth grades (Allison & Franklin, 1993).

Availability The DEBQ-R was originally printed in van Strien, Frijters, Bergers, et al. (1986).


Other Scales The RS, TFEQ-R, and DEBQ-R are typically the measures of choice when studying restrained eating. However, there are a few other scales worth mentioning, although most of the following lack much psychometric evidence to support their reliability or validity. One exception is the restraint scale of the Eating Disorders Examination, which is available in questionnaire (EDE-Q; Fairburn & Beglin, 1994) and interview (EDE; Fairburn & Cooper, 1993) forms. The EDE is primarily a diagnostic tool for anorexia and bulimia nervosa, for which its reliability and validity have been well demonstrated. However, the EDE is intended for use only in eating-disordered samples. As such, the restraint subscale is not appropriate for use with nonclinical samples. A restraint interview was created by Rand and Kuldau (1991) for use with nonclinical samples that may have certain advantages, including the potential for phone-based assessment and no requirement of reading skills on the part of the subject. Also, there is some thought that interviews may be less susceptible to dissimulation, given a skilled interviewer. Child versions of the RS and TFEQ were developed by Hill et al. (Hill, Rogers, & Blundell, 1989; Hill, Weaver, & Blundell, 1990). Other instruments that purport to measure restraint have been developed by Coker and Roger (1990) and Smead (1990).

Relationships Among the Restraint Scales Intercorrelations among the RS, TFEQ-R, and DEBQ-R are illustrated in Table 5.6. The TFEQ-R borrowed items from the RS, and the TFEQ-R and DEBQ-R both contain items from Pudel et al.’s (1975) Latent Obesity Scale. Thus, high correlations among the three restraint measures are not surprising. The correlations among measures appear to be similar for men and women. In contrast, correlations among scales appear to be lower for overweight than normal-weight individuals, especially for correlations between the RS and the other two scales. van Strien et al. (2007) report that the correlations between the RS (including the total score and both subscales) and the DEBQ-R and TFEQ-R are significantly lower for overweight women than normal-weight women. As discussed previously, the RS was not designed for use with overweight individuals and has questionable validity when used with this population. The lower correlations among restraint scales for overweight individuals are further evidence that the restraint constructs applied to normal-weight individuals do not translate perfectly to overweight samples. Wardle (1986) reported greater correlations between the DEBQ-R and the RS CD subscale (r = .75 for women and r = .76 for men) than the RS WF subscale (r = .24 for women and r = .37 for men). A similar pattern of results was reported by Boerner et al. (2004) for the relationship between the TFEQ-R and RS subscales, as well as by van Strien et al. (2007) for the RS subscales and both the TFEQ-R and DEBQ-R. These findings suggest that the three scales share common variance related to cognitive restraint but that the RS WF subscale measures a dimension that the other two scales do not address. The relationships among the three restraint measures have also been tested by conducting factor analyses on the scale scores for the restraint scales and sometimes other measures of eating behavior and weight concerns. For example, Allison et al. (1992) took the factors identified in factor analyses of each individual restraint scale and performed a second-order principal components factor analysis on these factors to look for overlap among the scales. The result was a three-factor solution. The first factor represented cognitive restraint and had high loadings from

176——HANDBOOK OF ASSESSMENT METHODS FOR EATING BEHAVIORS AND WEIGHT-RELATED PROBLEMS Table 5.6

Intercorrelations Among Restraint Scales

n

Coefficient alpha


901

.74

Obese and normal-weight college students


214

.63



Reference


RS and TFEQ-R

215

.68



60

.35

Normal-weight women

Ouwens, van Strien, and van der Staak (2003)

209

.73



200

.57


46

.51

Overweight men and women


349

.74



409

.35



901

.80



60

.59

Normal-weight women

Ouwens et at. (2003)

209

.69


Stice, Ozer, and Kees (1997)

117

.83



200

.55



46

.55



349

.71



409

.36


Wardle (1986)

147

.72


Wardle (1986)

147

.75


901

.89


RS and DEBQ-R

TFEQ and DEBQ-R 60

.66


Ouwens et at. (2003)

209

.85

Normal-weight women


200

.75



46

.69



349

.86



409

.66


Allison et al. (1992) Laessle et al. (1989)

Overweight, nonobese women NOTE: DEBQ-R = Dutch Eating Behavior Questionnaire–Restraint subscale; RS = Restraint Scale; TFEQ-R = Three-Factor Eating Questionnaire–Restraint scale.


the RS Concern With Dieting subscale, the DEBQ-R, and the TFEQ-R Factor I (cognitive restraint). The second factor consisted of Factor I (cognitive restraint) and Factor II (behavioral restraint) from the TFEQ-R and was therefore determined to be representative of a general restraint factor specific to the TFEQ-R. The third factor included only the RS Weight Fluctuation subscale. The authors concluded that the three scales share some common variance but that the TFEQ-R is the only scale that measures behavioral restraint, and the RS WF subscale is the only measure of weight fluctuation. Laessle et al. (1989) conducted a factor-analytic investigation that included the RS, the DEBQ-R, and the TFEQ restraint and disinhibition scales, as well as measures of weight history, self-reported mean daily caloric intake, disordered eating, and body figure consciousness. The first factor had high loadings from the RS, scales representing counterregulatory or disinhibited eating (the Eating Disorder Inventory Bulimia subscale and the TFEQ Disinhibition subscale), and measures representing body concern (Eating Disorder Inventory Body Dissatisfaction and Drive for Thinness subscales and the Body Shape Questionnaire). The second factor had high loadings from the RS and weight-related measures (BMI, maximum BMI, and a BMI fluctuation index). The third factor had high loadings from the TFEQ-R and the DEBQ-R, as well as a negative loading on mean caloric intake. van Strien et al. (2007), noting the three-factor solution obtained by Laessle et al. (1989), conducted a series of confirmatory factor analyses to determine how the three measures of restraint would load on three factors representing overeating, dieting, and body dissatisfaction. The overeating factor included the Eating Disorder Inventor Bulimia subscale, the DEBQ Emotional Eating and External Eating subscales, and the question, “Have you ever had an eating binge, i.e., you ate an amount of food others would consider unusually large?” The dieting factor included the question, “Are you currently dieting?” The body dissatisfaction factor included the Eating Disorder Inventory Drive for Thinness and Body Dissatisfaction subscales. The best-fit models for the TFEQ-R and DEBQ-R were the ones in which these scales loaded only on the dieting factor but not the overeating or body dissatisfaction factors. This was true for normal-weight and overweight subsamples. In contrast, the best-fit model for the RS was the one in which it loaded on all three factors, rather than just the dieting factor. There was an association between dieting and overeating in the normal-weight sample that was absent in the overweight sample. The results of Laessle et al. (1989) and van Strien et al. (2007) seem to confirm that the TFEQ-R and DEBQ-R are “purer” measures of restraint, whereas the RS taps constructs related to unsuccessful dieting such as overeating and weight fluctuation. Furthermore, the findings of van Strien et al. may explain why overweight individuals do not show disinhibited eating in preload studies; they lack the association between restraint and overeating that is present among normal-weight individuals.

Future Research Directions One priority for future research is improving our understanding of what the different restraint scales are actually measuring. Our review makes it clear that the RS reflects both the tendency to lose control over eating and the effort to resist that

tendency. The fact that the RS taps both tendencies simultaneously might be advantageous for some research questions, but the field’s understanding of factors that promote and inhibit overeating would be better served by research designs that analytically separate these two factors. Research that has categorized participants


on both the TFEQ disinhibition scale and the TFEQ restraint scale (e.g., Westenhoefer et al., 1994) represents one way of doing this. For the TFEQ-R and the DEBQ-R, it is becoming apparent that these scales do not identify individuals who are in negative energy balance or who are restricting their energy intake relative to unrestrained eaters (Stice et al., 2004, 2007). However, they may be restricting their intake relative to what they would like to eat (Lowe & Butryn, 2007). Although forced preloads do not elicit counterregulatory eating in restrained eaters identified by these scales, it is possible that such individuals would nonetheless show poorer eating regulation in situations in which multiple disinhibiting influences are operating simultaneously (e.g., a social gathering where alcohol and a variety of palatable foods are being consumed). It is possible that simply providing ice cream following a milkshake preload simply does not constitute a disinhibiting context powerful enough to overcome these restrained eaters’ efforts to avoid overconsumption (e.g., Jansen, 1996). Another major implication of the evidence reviewed in this chapter is that none of the measures of restrained eating reflects dieting as that term is usually understood—that is, losing weight by eating less than needed. Indeed, as Lowe (1993) suggested, “dieting to lose weight” and “restrained eating” appear to be two different constructs that are associated with different and sometimes opposing effects on behavior. Although measures of restrained eating have been shown to be related to a variety of domains (affective, cognitive, behavioral, physiological, and genetic), it cannot be assumed that these associations are due to hypocaloric dieting. Thus, future research is needed to study the effects of “restrained eating” separately from dieting (both in terms of self-labeled current dieting and documented weight loss dieting). Furthermore, if Lowe and Levine (2005) are correct that most restrained eating research should be interpreted in terms of the consequences of eating less than desired rather than eating less

than needed, then new explanations may be needed for many of the findings documented in the restraint literature. Finally, it is very important to keep in mind that the vast majority of research on restrained eating has been correlational in nature. This, of course, leaves open the question of whether restraint plays the causal role it is assumed to play in eating disregulation and eating disorders. Indeed, when dieting status has been experimentally manipulated, its effects are often opposite (e.g., Foster, Wadden, Kendall, Stunkard, & Vogt, 1996; Presnell & Stice, 2003) to those predicted by the original restraint model (Herman & Polivy, 1975, 1984). This suggests that restrained eating per se may not be responsible for the effects that are often associated with it. Alternatively, since most normal-weight restrained eaters are prone toward weight gain, it may be that restraint acts to moderate a predisposition toward weight gain such that restraint slows but usually does not prevent eventual weight gain. Also, it is important to keep in mind that, to the extent that restrained eating does have causal effects on behavior, they may be quite different depending on why a person is attempting to exercise dietary restraint. For example, an anorexic restrictor, a normal-weight person who is struggling to avoid weight gain, and an obese binge eater may all be “restrained eaters,” but the form and consequences of such restraint may be quite different in each.

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